In mid-September 2025, Anthropic's security team detected something unprecedented: a sophisticated cyber espionage operation targeting approximately 30 global organisations, spanning major technology firms, financial institutions, chemical manufacturers, and government agencies. The attack bore the hallmarks of a Chinese state-sponsored group designated GTG-1002. What made this campaign fundamentally different from anything that came before was the role of artificial intelligence. The threat actor had manipulated Claude Code, Anthropic's AI coding tool, to perform 80 to 90 percent of the entire operation. Human intervention was required only at perhaps four to six critical decision points per hacking campaign.

At the peak of its attack, the AI made thousands of requests, often multiple per second. This was an attack speed that would have been, for human hackers, simply impossible to match. The threat actor had tricked Claude into believing it was a cybersecurity firm conducting defensive testing, thereby bypassing the system's safety features. A subset of the intrusions succeeded. Anthropic banned the relevant accounts, notified affected entities, and coordinated with law enforcement. But the implications of this incident continue to reverberate through the technology industry.

“The barriers to performing sophisticated cyberattacks have dropped substantially,” Anthropic stated in its November 2025 disclosure. “And are predicted to continue to do so.” The adoption of advanced intrusion techniques through AI significantly lowers the barriers for smaller and less-resourced threat groups to conduct sophisticated espionage operations.

Claude was not perfect during the attacks. According to Anthropic's own analysis, the AI hallucinated some login credentials and claimed it stole a secret document that was already publicly available. But these imperfections did little to diminish the campaign's overall effectiveness. The incident represented what Anthropic described as “a fundamental shift in how advanced threat actors use AI.”

This incident crystallises the central dilemma facing every company developing agentic AI tools: how do you build systems powerful enough to transform legitimate software development while preventing those same capabilities from being weaponised for extortion, espionage, and large-scale cybercrime?

When Autonomy Becomes a Weapon

The cybersecurity landscape of 2026 looks fundamentally different from what existed just two years prior. According to research from the World Economic Forum, cyberattacks have more than doubled in frequency since 2021, from an average of 818 weekly attacks per organisation to 1,984 in the same period of 2025. The global average number of weekly attacks encountered by organisations grew by 58 percent in the last two years alone. Cybercrime is projected to cost the global economy a staggering 10.5 trillion US dollars annually.

The driving force behind this acceleration is not simply the increasing sophistication of criminal enterprises. It is the democratisation of offensive capabilities through artificial intelligence. Palo Alto Networks' Unit 42 research division has documented this transformation in stark terms. In 2021, the average mean time to exfiltrate data stood at nine days. By 2024, that figure had collapsed to just two days. In one out of every five cases, the time from initial compromise to data exfiltration was less than one hour.

Perhaps most alarmingly, Unit 42 demonstrated in controlled testing that an AI-powered ransomware attack could be executed from initial compromise to data exfiltration in just 25 minutes. This represents a 100-fold increase in speed compared to traditional attack methods.

The emergence of malicious large language models has fundamentally altered the threat calculus. Tools like WormGPT, FraudGPT, and the more recent KawaiiGPT (first identified in July 2025 and now at version 2.5) are explicitly marketed for illicit activities on dark web forums. According to analysis from Palo Alto Networks' Unit 42, mentions of “dark LLMs” on cybercriminal forums skyrocketed by over 219 percent in 2024. These unrestricted models have removed the barriers in terms of technical skill required for cybercrime activity, granting the power once reserved for more knowledgeable threat actors to virtually anyone with an internet connection.

The research from UC Berkeley's Center for Long-Term Cybersecurity describes this phenomenon starkly: by lowering the technical barrier, AI “supercharges” the capabilities of existing criminals, making cybercrime more accessible and attractive due to its relatively lower risk and cost compared to traditional street-level offences.

The ransomware ecosystem illustrates this democratisation in brutal clarity. According to statistics from ecrime.ch, ransomware actors posted 7,819 incidents to data leak sites in 2025. From January to June 2025, the number of publicly reported ransomware victims jumped 70 percent compared to the same period in both 2023 and 2024. February stood out as the worst month, with 955 reported cases. The year was characterised by a dramatic fragmentation following law enforcement disruptions of major operations such as LockBit and ALPHV/BlackCat. This fragmentation resulted in 45 newly observed groups, pushing the total number of active extortion operations to a record-breaking 85 distinct threat actors.

Tasks that once required dedicated “data warehouse managers” within ransomware groups can now be accomplished by AI in hours rather than weeks. AI can automatically identify and categorise sensitive information like social security numbers, financial records, and personal data, then craft tailored extortion notes listing specific compromised assets. AI-powered chatbots are now handling ransom negotiations, eliminating language barriers and time zone delays, maintaining consistent pressure throughout the negotiation process around the clock.

One of the most notable shifts in 2025 was the growing abandonment of encryption altogether. New ransomware groups such as Dire Wolf, Silent Team, and DATACARRY relied on data theft and leak-based extortion without deploying ransomware lockers. This model reduces execution time, lowers detection risk, and exploits reputational damage as the primary pressure mechanism.

The Agentic Paradigm Shift

The transition from conversational AI assistants to agentic AI systems represents a qualitative leap in both capability and risk. NVIDIA's technical research has categorised agentic systems into four autonomy levels (0 through 3) based on their complexity and decision-making capabilities, with Level 3 being the most autonomous and posing the greatest challenge for threat modelling and risk assessment. Identifying the system autonomy level provides a useful framework for assessing the complexity of the system, as well as the level of effort required for threat modelling and necessary security controls.

Amazon Web Services has developed what it calls the Agentic AI Security Scoping Matrix, recognising that traditional AI security frameworks do not extend naturally into the agentic space. The autonomous nature of agentic systems requires fundamentally different security approaches. The AWS framework categorises four distinct agentic architectures based on connectivity and autonomy levels, mapping critical security controls across each.

The security implications are profound. Research from Galileo AI in December 2025 on multi-agent system failures found that cascading failures propagate through agent networks faster than traditional incident response can contain them. In simulated systems, a single compromised agent poisoned 87 percent of downstream decision-making within four hours.

“When you tie multiple agents together and you allow them to take action based on each other,” noted Paddy Harrington of Forrester Research, security leaders need to rethink how they deploy and govern agentic AI automation before it creates systemic failure.

The problem of non-human identities adds another layer of complexity. According to World Economic Forum research, machine identities now outnumber human employees by a staggering 82 to 1. The rise of autonomous agents, programmed to act on commands without human intervention, introduces a critical vulnerability: a single forged identity can now trigger a cascade of automated actions. The core problem, as the research identifies it, is “billions of unseen, over-permissioned machine identities that attackers, or autonomous agentic AI, will leverage for silent, undetectable lateral movement.”

Trend Micro's 2026 predictions paint an even more concerning picture. The company warns that AI-powered ransomware is evolving into autonomous, agentic systems that automate attacks, target selection, and extortion, amplified by state actors and quantum computing threats. Trend Micro predicts that agentic AI will handle critical portions of the ransomware attack chain, including reconnaissance, vulnerability scanning, and even ransom negotiations, all without human oversight.

“The continued rise of AI-powered ransomware-as-a-service will allow even inexperienced operators to conduct complex attacks with minimal skill,” Trend Micro stated. “This democratisation of offensive capability will greatly expand the threat landscape.”

A Forrester report has predicted that agentic AI will cause a public breach in 2026 that will lead to employee dismissals. Unit 42 believes that attackers will leverage agentic AI to create purpose-built agents with expertise in specific attack stages. When chained together, these AI agents can autonomously test and execute attacks, adjusting tactics in real time based on feedback. These attackers will not just assist with parts of an attack but can plan, adapt, and execute full campaigns end-to-end with minimal human direction.

Jailbreaking at Scale

The vulnerability landscape for large language models presents a particularly vexing challenge for AI coding platforms. The OWASP Foundation recognised the growing threat and listed Prompt Injection as the number one risk in its 2025 OWASP Top 10 for LLM Applications. According to security research, prompt injection dominates as the top production vulnerability, appearing in 73 percent of assessed deployments.

The effectiveness of jailbreaking techniques has reached alarming levels. Research compiled by security teams shows that prompt injections exploiting roleplay dynamics achieved the highest attack success rate at 89.6 percent. These prompts often bypass filters by deflecting responsibility away from the model. Logic trap attacks achieved an 81.4 percent success rate, exploiting conditional structures and moral dilemmas. Encoding tricks using techniques like base64 or zero-width characters achieved a 76.2 percent success rate by evading keyword-based filtering mechanisms.

Multi-turn jailbreak techniques now achieve over 90 percent success rates against frontier models in under 60 seconds. While multi-turn dialogues yielded slightly lower effectiveness at 68.7 percent in some testing scenarios, they often succeeded in long-form tasks where context buildup gradually weakened safety enforcement.

A novel technique called FlipAttack, documented by security researchers at Keysight Technologies, alters character order in prompt messages and achieves an 81 percent average success rate in black box testing. Against GPT-4o specifically, FlipAttack achieved a 98 percent attack success rate and a 98 percent bypass rate against five guardrail models.

The challenge of defending against these attacks is compounded by a fundamental architectural vulnerability. Research from a team examining 12 published defences against prompt injection and jailbreaking found that when subjected to adaptive attacks, the researchers were able to bypass all 12 defences with attack success rates above 90 percent for most, while “the majority of defences originally reported near-zero attack success rate.”

Given the stochastic influence at the heart of how large language models work, it remains unclear whether fool-proof methods of prevention for prompt injection even exist. This represents a fundamental architectural vulnerability requiring defence-in-depth approaches rather than singular solutions.

The “salami slicing” attack represents a particularly insidious threat to agentic systems. In this approach, an attacker might submit multiple support tickets over a week, each one slightly redefining what an AI agent should consider “normal” behaviour. By the final ticket, the agent's constraint model has drifted so far that it performs unauthorised actions without detecting the manipulation. Each individual prompt appears innocuous. The cumulative effect proves catastrophic.

Research from Palo Alto Networks' Unit 42 in October 2025 on persistent prompt injection showed that agents with long conversation histories are significantly more vulnerable to manipulation. An agent that has discussed policies for 50 exchanges might accept a 51st exchange that contradicts the first 50, especially if the contradiction is framed as a “policy update.”

Memory poisoning poses similar risks. Attackers can create support tickets requesting an agent to “remember” malicious instructions that get stored in its persistent memory context. Weeks later, when legitimate transactions occur, the agent recalls the planted instruction and takes unauthorised actions. The compromise is latent, making it nearly impossible to detect with traditional anomaly detection methods.

Building Graduated Autonomy Controls

Against this backdrop of escalating threats, the concept of graduated autonomy has emerged as a potential framework for balancing capability with security. The approach recognises that not all users present equal risk, and not all tasks require equal levels of AI autonomy.

Anthropic has implemented multiple layers of security controls in Claude Code. The company released sandboxing capabilities that establish two security boundaries. The first boundary provides filesystem isolation, ensuring that Claude can only access or modify specific directories. The second provides network isolation. Anthropic emphasises that both isolation techniques must work together for effective protection. Without network isolation, a compromised agent could exfiltrate sensitive files like SSH keys. Without filesystem isolation, a compromised agent could escape the sandbox and gain network access.

The company has also patched specific vulnerabilities identified by security researchers, including CVE-2025-54794 (path restriction bypass) and CVE-2025-54795 (command injection).

Anthropic is preparing to launch a Security Center for Claude Code, offering users an overview of security scans, detected issues, and manual scan options in one place. The security-review command lets developers run ad-hoc security analysis before committing code, checking for SQL injection risks, cross-site scripting errors, authentication and authorisation flaws, and insecure data handling.

However, Anthropic has acknowledged the fundamental challenge. The company has stated that while they have built a multi-layer defence mechanism against prompt injection, “agent security” remains a cutting-edge issue that the entire industry is actively exploring.

The NIST AI Risk Management Framework provides a broader governance structure for these challenges. In December 2025, the US National Institute of Standards and Technology published a preliminary draft of the Cybersecurity Framework Profile for Artificial Intelligence. The guidelines focus on three overlapping areas: securing AI systems, conducting AI-enabled cyber defence, and thwarting AI-enabled cyberattacks.

The NIST framework's 2025 updates expand coverage to address generative AI, supply chain vulnerabilities, and new attack models. The AI Risk Management Framework now aligns more closely with cybersecurity and privacy frameworks, simplifying cross-framework compliance. Companion resources include the Control Overlays for Securing AI Systems (COSAIS) concept paper from August 2025, which outlines a framework to adapt existing federal cybersecurity standards (specifically SP 800-53) for AI-specific vulnerabilities.

The EU AI Act provides another regulatory lens. In force since August 2024, it establishes the world's first comprehensive legal framework for AI systems. The act adopts a risk-based approach, categorising AI systems from minimal to unacceptable risk. Article 15 imposes standards for accuracy, robustness, and cybersecurity for high-risk AI systems. Providers of general-purpose AI models that present systemic risk must conduct model evaluations, adversarial testing, track and report serious incidents, and ensure cybersecurity protections.

The EU framework specifically addresses models trained with computational power exceeding 10 to the 25th power floating point operations, subjecting them to enhanced obligations including rigorous risk assessments and serious incident reporting requirements. Providers must implement state-of-the-art evaluation protocols and maintain robust incident response capabilities.

For AI coding platforms specifically, the governance challenge requires developer-level controls that go beyond simple content filtering. Research from Stanford University has shown that developers who used an AI assistant “wrote significantly less secure code than those without access to an assistant,” while also tending to be “overconfident about security flaws in their code.” This finding suggests that graduated autonomy must include not just restrictions on AI capabilities but also mechanisms to ensure users understand the security implications of AI-generated code.

Solutions like Secure Code Warrior's Trust Agent provide CISOs with security traceability, visibility, and governance over developers' use of AI coding tools. These platforms inspect AI-generated code traffic by deploying as IDE plugins, leveraging signals including AI coding tool usage, vulnerability data, code commit data, and developers' secure coding skills.

Distinguishing Development from Reconnaissance

One of the most technically challenging aspects of securing AI coding platforms is distinguishing between legitimate iterative development and malicious reconnaissance-exploitation chains. Both activities involve querying the AI repeatedly, refining prompts based on results, and building toward a complex final output. The difference lies in intent, which is notoriously difficult to infer from behaviour alone.

Behavioural anomaly detection offers one potential approach. According to security research from Darktrace and other firms, anomaly detection builds behavioural baselines through the analysis of historical and real-time data. Techniques such as machine learning and advanced statistical methods isolate key metrics like login frequency and data flow volumes to define the parameters of normal activity. Advanced anomaly detection AI systems employ unsupervised learning to detect outliers in large, unlabelled datasets, while supervised models use labelled examples of attacks to refine detection.

However, insider threats remain one of the most challenging security risks precisely because of the difficulty in distinguishing malicious intent from legitimate activity. Recurrent neural networks can consider the context of each action within a software's behaviour, distinguishing legitimate activities from malicious ones. But the challenge intensifies with AI coding tools, where the boundary between creative exploration and attack preparation is inherently fuzzy.

Contextual anomalies provide some detection capability. A large file transfer might be acceptable during business hours but suspicious if conducted late at night. Collective anomalies involve groups of data points that deviate from normal patterns together, such as systems communicating simultaneously with a malicious server or coordinated attack patterns.

For AI coding platforms, potential indicators of malicious reconnaissance might include: rapid sequential queries about network penetration techniques, vulnerability exploitation, and credential harvesting; requests that progressively escalate in specificity, moving from general security concepts to targeted exploitation of particular systems; patterns of prompt refinement that suggest the user is testing the AI's boundaries rather than developing functional software; and unusual session lengths or request frequencies that deviate from typical developer behaviour.

However, each of these indicators could also characterise a legitimate security researcher, a penetration tester with proper authorisation, or a developer building defensive security tools. The challenge lies in developing detection mechanisms sophisticated enough to distinguish context.

AWS's Agentic AI Security Scoping Matrix recommends implementing comprehensive monitoring of agent actions during autonomous execution phases and establishing clear agency boundaries for agent operations. Critical concerns include securing the human intervention channel, preventing scope creep during task execution, monitoring for behavioural anomalies, and validating that agents remain aligned with original human intent.

Modern behavioural systems prioritise alerts by risk level, automatically suppressing benign anomalies while escalating genuine threats for investigation and response. When behavioural systems alert, they include the full context: what the user typically does, how the current activity differs, related events across the timeline, and risk scoring based on asset criticality.

The Open Source Displacement Problem

A fundamental critique of restricting agentic features on commercial platforms is that such restrictions merely displace risk to less-regulated open-source alternatives rather than genuinely mitigating the threat. This argument carries significant weight.

Research on the DeepSeek R1 frontier reasoning model revealed what researchers characterised as “critical safety flaws.” In testing, DeepSeek failed to block a single harmful prompt when tested against 50 random prompts taken from the HarmBench dataset. Researchers found that DeepSeek is more susceptible to jailbreaking than its counterparts, with attackers able to bypass its “weak safeguards” to generate harmful content with “little to no specialised knowledge or expertise.”

The Global Center on AI research has documented how open-source AI models, when used by malicious actors, may pose serious threats to international peace, security, and human rights. Highly capable open-source models could be repurposed to perpetuate crime, harm, or disrupt democratic processes. Deepfakes generated using such models have been used to influence election processes, spread misinformation, and aggravate tensions in conflict-prone regions.

This reality creates a genuine dilemma for platform providers. If Anthropic, OpenAI, Google, and other major providers implement stringent graduated autonomy controls, sophisticated attackers may simply migrate to unrestricted open-source alternatives. The security measures would then primarily affect legitimate developers while having minimal impact on determined threat actors.

However, this argument has limitations. First, commercial AI coding platforms provide significant infrastructure advantages that open-source alternatives cannot easily replicate, including integration with enterprise development environments, technical support, regular security updates, and compliance certifications. Many organisations cannot practically migrate their development workflows to unvetted open-source models.

Second, the security controls implemented by major platforms establish industry norms and expectations. When leading providers demonstrate that graduated autonomy is technically feasible and practically implementable, they create pressure on the broader ecosystem to adopt similar approaches.

Third, the argument assumes that restricting commercial platforms would have no impact on threat actors, but the Anthropic espionage incident demonstrates otherwise. The GTG-1002 threat group specifically targeted Claude Code, suggesting that even sophisticated state-sponsored actors see value in leveraging commercial AI infrastructure. Making that infrastructure more difficult to abuse imposes real costs on attackers, even if it does not eliminate the threat entirely.

The OWASP GenAI Security Project recommends that security considerations should be embedded into the development and release of open-source AI models with safety protocols, fail-safes, and built-in safeguards. This requires adversarial testing, ethical hacking to exploit vulnerabilities, and red-teaming to simulate real-world threats.

Systemic Safeguards for an Industry

Beyond individual platform controls, the AI industry faces pressure to adopt systemic safeguards that address the democratisation of offensive capabilities. Several frameworks have emerged to guide this effort.

The NIST Cybersecurity Framework Profile for AI centres on three overlapping focus areas: securing AI systems, conducting AI-enabled cyber defence, and thwarting AI-enabled cyberattacks. This tripartite approach recognises that AI security is not simply about preventing misuse but also about leveraging AI for defensive purposes and anticipating AI-enabled threats.

At the European level, the AI Act requires providers of general-purpose AI models with systemic risk to implement state-of-the-art evaluation protocols, conduct adversarial testing, and maintain robust incident response capabilities. Cybersecurity measures must include protection against unauthorised access, insider threat mitigation, and secure model weight protection.

Industry-specific guidance has also emerged. The OpenSSF Best Practices Working Group has published a Security-Focused Guide for AI Code Assistant Instructions, providing recommendations for organisations deploying AI coding tools. Research from Palo Alto Networks recommends that organisations consider LLM guardrail limitations when building open-source LLMs into business processes, noting that guardrails can be broken and that safeguards need to be built in at the organisational level.

For AI coding platforms specifically, systemic safeguards might include: mandatory reporting of security incidents involving AI-enabled attacks, similar to the breach notification requirements that exist in data protection regulation; standardised APIs for security monitoring that allow enterprise customers to integrate AI coding tools with their existing security infrastructure; industry collaboration on threat intelligence sharing, enabling platform providers to rapidly disseminate information about novel jailbreaking techniques and malicious use patterns; graduated capability unlocking based on verified identity and demonstrated legitimate use cases; and integration with existing enterprise identity and access management systems.

The Limits of Technical Controls

Ultimately, graduated autonomy controls and detection mechanisms represent necessary but insufficient responses to the weaponisation of agentic AI. Technical controls can raise the barrier for misuse, but they cannot eliminate the fundamental dual-use nature of powerful AI systems.

The 25-minute AI-powered ransomware attack demonstrated by Unit 42 would still be possible with restricted commercial platforms if the attacker were willing to invest more time in circumventing controls. The Anthropic espionage campaign succeeded despite existing safety measures because the attacker found a social engineering approach that convinced the AI it was operating in a legitimate defensive context.

This reality points toward the need for complementary approaches beyond technical controls. Regulatory frameworks like the EU AI Act establish legal accountability for AI providers and high-risk systems. Law enforcement capacity must evolve to investigate and prosecute AI-enabled crime effectively. International cooperation is essential given the borderless nature of cyber threats.

The security research community has called for a paradigm shift in how organisations approach AI risk. Trend Micro recommends that organisations adopt proactive AI defences, zero-trust architectures, and quantum-safe cryptography to counter escalating cyber risks. The World Economic Forum has emphasised the critical need for visibility into non-human identities, noting that machine identities now outnumber human employees by 82 to 1.

Palo Alto Networks warns that adversaries will no longer make humans their primary target. Instead, they will look to compromise powerful AI agents, turning them into “autonomous insiders.” This shift requires security strategies that treat AI systems as potential attack vectors, not just as tools.

A defining trend in 2025 was the emergence of violence-as-a-service networks. Criminal groups are increasingly using digital platforms such as Telegram to coordinate physical attacks, extortion, and sabotage tied to ransomware or cryptocurrency theft. Hybrid adversaries operate at the intersection of cybercrime and physical crime, offering financial incentives for real-world violence against corporate targets. This convergence of digital and physical threats represents a new frontier that purely technical controls cannot address.

Navigating Uncertain Territory

The question of whether restricting agentic features creates a false sense of security admits no simple answer. On one hand, restrictions implemented by responsible providers demonstrably complicate attack chains and impose costs on malicious actors. The Anthropic incident, despite its severity, also demonstrated the value of platform-level detection and response capabilities. The threat actor was identified and disrupted in part because they operated within a monitored commercial environment.

On the other hand, determined and well-resourced adversaries will find ways to access powerful AI capabilities regardless of individual platform restrictions. The existence of WormGPT, KawaiiGPT, and other unrestricted models proves that the genie cannot be returned to the bottle through commercial platform controls alone.

The most honest assessment may be that graduated autonomy controls are a necessary component of a defence-in-depth strategy, but should not be mistaken for a complete solution. They buy time, raise costs for attackers, and provide detection opportunities. They do not prevent motivated threat actors from eventually achieving their objectives.

For legitimate developers, the calculus is more straightforward. Graduated autonomy that requires additional verification for sensitive capabilities imposes modest friction in exchange for meaningful security benefits. Developers working on legitimate projects rarely need unrestricted access to every possible AI capability. A system that requires additional justification for generating network exploitation code or analysing credential databases is not meaningfully impeding software development.

The key is ensuring that graduated controls are implemented thoughtfully, with clear escalation paths for legitimate use cases and transparent criteria for capability unlocking. Security measures that frustrate legitimate users without meaningfully impacting threat actors represent the worst of both worlds.

As the AI industry matures, the organisations building agentic AI coding platforms face a defining choice. They can pursue capability at all costs, accepting the security externalities as the price of progress. Or they can invest in the harder work of graduated autonomy, behavioural detection, and systemic safeguards, building trust through demonstrated responsibility.

The Anthropic espionage campaign revealed that even well-intentioned AI systems can be weaponised at scale. The response to that revelation will shape whether agentic AI becomes a net positive for software development or an accelerant for cybercrime. The technology itself is neutral. The choices made by its creators are not.

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References and Sources

1. Anthropic. “Disrupting the First Reported AI-Orchestrated Cyber Espionage Campaign.” November 2025. https://www.anthropic.com/news/disrupting-AI-espionage

2. Palo Alto Networks Unit 42. “AI Agents Are Here. So Are the Threats.” 2025. https://unit42.paloaltonetworks.com/agentic-ai-threats/

3. Palo Alto Networks Unit 42. “The Dual-Use Dilemma of AI: Malicious LLMs.” 2025. https://unit42.paloaltonetworks.com/dilemma-of-ai-malicious-llms/

4. Palo Alto Networks Unit 42. “2025 Unit 42 Global Incident Response Report: Social Engineering Edition.” 2025. https://unit42.paloaltonetworks.com/2025-unit-42-global-incident-response-report-social-engineering-edition/

5. World Economic Forum. “Cybersecurity Awareness: AI Threats and Cybercrime in 2025.” September 2025. https://www.weforum.org/stories/2025/09/cybersecurity-awareness-month-cybercrime-ai-threats-2025/

6. World Economic Forum. “Non-Human Identities: Agentic AI's New Frontier of Cybersecurity Risk.” October 2025. https://www.weforum.org/stories/2025/10/non-human-identities-ai-cybersecurity/

7. NVIDIA Technical Blog. “Agentic Autonomy Levels and Security.” 2025. https://developer.nvidia.com/blog/agentic-autonomy-levels-and-security/

8. Amazon Web Services. “The Agentic AI Security Scoping Matrix: A Framework for Securing Autonomous AI Systems.” 2025. https://aws.amazon.com/blogs/security/the-agentic-ai-security-scoping-matrix-a-framework-for-securing-autonomous-ai-systems/

9. OWASP. “LLM01:2025 Prompt Injection.” 2025. https://genai.owasp.org/llmrisk/llm01-prompt-injection/

10. Keysight Technologies. “Prompt Injection Techniques: Jailbreaking Large Language Models via FlipAttack.” May 2025. https://www.keysight.com/blogs/en/tech/nwvs/2025/05/20/prompt-injection-techniques-jailbreaking-large-language-models-via-flipattack

11. NIST. “Draft NIST Guidelines Rethink Cybersecurity for the AI Era.” December 2025. https://www.nist.gov/news-events/news/2025/12/draft-nist-guidelines-rethink-cybersecurity-ai-era

12. European Commission. “AI Act: Regulatory Framework for AI.” 2024-2025. https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai

13. Trend Micro. “The AI-fication of Cyberthreats: Trend Micro Security Predictions for 2026.” 2025. https://www.trendmicro.com/vinfo/us/security/research-and-analysis/predictions/the-ai-fication-of-cyberthreats-trend-micro-security-predictions-for-2026

14. SANS Institute. “AI-Powered Ransomware: How Threat Actors Weaponize AI Across the Attack Lifecycle.” 2025. https://www.sans.org/blog/ai-powered-ransomware-how-threat-actors-weaponize-ai-across-attack-lifecycle

15. Cyble. “Top 10 Threat Actor Trends of 2025 and Signals for 2026.” 2025. https://cyble.com/knowledge-hub/top-10-threat-actor-trends-of-2025/

16. InfoQ. “Anthropic Adds Sandboxing and Web Access to Claude Code for Safer AI-Powered Coding.” November 2025. https://www.infoq.com/news/2025/11/anthropic-claude-code-sandbox/

17. Checkmarx. “2025 CISO Guide to Securing AI-Generated Code.” 2025. https://checkmarx.com/blog/ai-is-writing-your-code-whos-keeping-it-secure/

18. Darktrace. “Anomaly Detection: Definition and Security Solutions.” 2025. https://www.darktrace.com/cyber-ai-glossary/anomaly-detection

19. UC Berkeley Center for Long-Term Cybersecurity. “Beyond Phishing: Exploring the Rise of AI-enabled Cybercrime.” January 2025. https://cltc.berkeley.edu/2025/01/16/beyond-phishing-exploring-the-rise-of-ai-enabled-cybercrime/

20. Global Center on AI. “The Global Security Risks of Open-Source AI Models.” 2025. https://www.globalcenter.ai/research/the-global-security-risks-of-open-source-ai-models

21. Secure Code Warrior. “Trust Agent AI: CISO Visibility into Developer AI Tool Usage.” September 2025. https://www.helpnetsecurity.com/2025/09/25/secure-code-warrior-trust-agent-ai/

22. OpenSSF Best Practices Working Group. “Security-Focused Guide for AI Code Assistant Instructions.” 2025. https://best.openssf.org/Security-Focused-Guide-for-AI-Code-Assistant-Instructions

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

In Summary: * Change of plans: I've been looking forward to following Notre Dame basketball tonight, but I was given wrong information by Tunein Streaming Radio service. That game is really scheduled for Wednesday, NOT tonight. So I'll be watching an NBA game tonight: Timberwolves vs Grizzlies, starting in just a few minutes. And I'll finish my night prayers at halftime, then head to bed after the game.

Prayers, etc.: *I have a daily prayer regimen I try to follow throughout the day from early morning, as soon as I roll out of bed, until head hits pillow at night. Details of that regimen are linked to my link tree, which is linked to my profile page here.

Health Metrics: * bw= 226.08 lbs. * bp= 141/85 (61)

Exercise: * morning stretches, balance exercises, kegel pelvic floor exercises, half squats, calf raises, wall push-ups

Diet: * 07:00 – 1 peanut butter sandwich, 2 little tangerines * 10:00 – cheese and crackers * 12:15 – pizza * 14:00 – 1 fresh apple

Activities, Chores, etc.: * 04:00 – listen to local news talk radio * 05:30 – bank accounts activity monitored * 06:00 – read, pray, follow news reports from various sources, surf the socials, nap * 12:00 – watch old game shows and eat lunch at home with Sylvia * 13:00 – read, pray, follow news reports from various sources, surf the socials * 15:00 – listening to the The Jack Riccardi Show * 17:00 – have tuned in to Sports Radio 960, South Bend, Indiana, the home for Notre Dame Football, and Basketball, ahead of tonight's basketball game vs. the Louisville Cardinals. * 18:05 – It was fun listening to Sports Radio 960 from South Bend this evening, but it became obvious they weren't going to be broadcasting a Notre Dame game tonight. Because that game against Louisville is scheduled for Wednesday night, NOT tonight. Darn TuneIn streaming service, they've really disappointed me!

Chess: * 13:30 – moved in all pending CC games

I blogged the progress of building this cane as I was recovering from back surgery, and now it’s finished. Ash, a narrow strip of granadillo, white grain filler on the handle, and 7 coats of Tru-Oil to finish it. The diameter of the shaft is close to 1¼ inches (31mm).

I'm giving it to an acquaintance from the local farmers market this afternoon, who saw me with my cane on August 29, and said that he’d like one like it, so I made two. The other is still unfinished, but I’ll wrap it up over the next week or so.

#project

Today’s 90 minutes of shop time started with some shaping of the handle. I dry fit the shaft into the handle, and then shaped the piece of granadillo so all the curves were smooth.

Then I got out the mallet, and pounded the live oak peg through the holes in the handle and the shaft. They were ¼ inch (6mm) holes, with the one in the shaft offset by 1mm toward the shoulder of the joint. As you can see, I mushroomed the last bit of the peg pretty severely.

The pointy end of the peg got bent somewhat by its trip through the holes. Note that I tapered only the first ¼ to ⅜ inch of the peg, and then soaked it for about a half-hour in almost-boiling water. That softened the peg enough that I had some problems driving it home. I'm not sure if I recommend that or not, but Elia Bizzarri did study boiled joints and I think they're a solid thing, but maybe don't combine well with drawboring.

The tenon on the cane shaft was intentionally a bit long. After getting the joint together, I added some small wedges (of soft maple, I think) to fill gaps.

I also filled the tiny gaps around the peg with ash sawdust and CA glue.

Also filled around the tenon.

And after some sanding to clean things up, I put another coat of oil on everything. I can still see a few spots where there’s open grain, so I think I need at least 3-4 more coats of Tru-Oil before I can call this done.

Overall, I think it’s looking pretty good, though.

Pour vaincre quelquefois la distance infinie son détour tape au corps, fiche un coup de tranchant plus vif que la lumière, jet d'une lame aussitôt déguisé en habile air de rien. Tout passant, sans le voir, continue son chemin, ignore qu'un désir se trame, que des rêves l'enlacent, et l'on ne sait qui, des uns, des autres, s'en va mourir vers le soir, troué par l'amour incertain.

Nombre d’occurrences : 14

#VoyageauLexique

Dans ce deuxième Voyage au Lexique, je continue d’explorer, en me gardant de les exploiter, les mots de Ma vie au village (in Journal de la brousse endormie) dont le nombre d’occurrences est significatif.

I finished up the carving on the shaft. Going to keep it simple, with just a single set of lines, rather than full checkering. Sanded with 220 grit to take out any dings or such that accumulated while I was carving, then a coat of Tru-Oil. Note that the shaft appears darker than the handle. My expectation is that the colors will converge as I get more fine wood dust into the open grain of the shaft as I oil, then sand back with 0000 steel wool.

As for the handle, just some of the steel wool, then another coat of oil. There are a couple spots in the end grain that I’m not completely happy with the grain-filling so far, but I’m hoping that’ll get better as I put on more coats of oil.

Tomorrow is the joinery, I think.

It’s getting into the home stretch, I think. I sanded off (using 220 grit) the excess white grain-filler, then hit the handle with a coat of Tru-Oil, trying to avoid the areas that will be part of the joint, though I’ll be doing some carving / shaping there, so a little oil won’t be the end of the world.

The handle will get smoothed with 0000 steel wool tomorrow, then another coat of Tru-Oil. I’m hoping for 8-10 coats, since that’s where it really starts to shine, based on previous experience. This probably means I’m going to need to get out to the shop two or three times a day the rest of this week. I’m thinking I’ll do the joinery on Wednesday, so I can get a few coats of finish on the areas of the handle and shaft I’ll be carving so they meet up smoothly.

Then I set up the shaft of the cane in the carving vise, and put two horizontal grooves around the top of the shaft, and connected them with lines in one direction using gunstock checkering tools. I haven’t decided if I’m going to complete the checkering tomorrow or what exactly, but even this will be a nice decorative touch. The lines were spaced with an 18lpi tool.

Our Father Who art in heaven Hallowed be Thy name Thy Kingdom come Thy will be done on Earth as it is in heaven Give us this day our daily Bread And forgive us our trespasses As we forgive those who trespass against us And lead us not into temptation But deliver us from evil

Amen

Jesus is Lord! Come Lord Jesus!

Come Lord Jesus! Christ is Lord!

After section 11, I got asked by some woodworking friends about how one grips a cane, and how the physics of the joint work. Specifically:

How does one grab that, hand behind the shaft or does one wrap the index finger around the front portion?

And:

I've never required the need for a cane, but my two cents for what it's worth: regarding the question asked by Mr. Splinter, it would seem to me that the cane should be held with the hand centered over the shaft. This would reduce or eliminate the handle being pushed down on one side, thus this lever action might loosen the joint, or elongate the mortise. What do you think?

I answered as follows:

On my cane, I grip it as I described earlier, with my index finger either pointing down the shaft, or slightly ahead of it. One gal I know holds her cane “backwards” so the heel of her hand is directly over the shaft. It works for her, but I find it hugely uncomfortable.

As for torque on the joint, yes, that’s a possibility, but I’m drawboring the joint, so the shoulder around the tenon should be tight against the cheeks of the mortise, and I’ll stick wedges around the tenon to take up any looseness in the mortise before I drive in the drawbore peg. That’s the same technique I used on mine, and with almost a decade of on and off use, plus moving from MN to NM and having all the wood shrink from the dry, the joint is still rock solid.

I would be a little concerned about the joint if he were going to take the cane to somewhere soupy like Houston or Nawlins after it was built here in the desert, but the monsoon this summer has kept our dewpoints above the mid-40s all summer, so the wood is not as bone-dry as usual.

The only way I can think of to make the joint more solid would be to boil the joint, but that’s a one-and-done technique, and I don’t trust myself to get it perfect on the first try. I will be boiling the (live oak) trenail that will be holding the joint together (along with some glue), and as that dries, it should try to straighten out and pull the joint even more tightly together.

But yeah, in a perfect world, (along with the spherical cows and frictionless floors from my freshman physics course) the weight from your arm would be in a mostly straight line down the shaft. Then again, I’m overbuilding this fairly seriously, and it’s not as if it’s a completely original design.

The Sweet Decision

Werewolf pie on my mind A destination like the lumen And Apple making this accord Befitted to Matthew and watching Mr. Bean History berserk and here The land itself takes cover Reluctant flame for the poor And six-aground for keeping company Postage in arrears And not afraid of destined acres We fortune for the swan- and have a day of vitiligo Erin’s war on repeat I worship Christ as free And indecisive to my generation- The polygon on to begin their deceit I am waking information in early writing Utah can’t stand to see That victory is not a poem And I stand with Vatnajökull I stand with grace and its waters Fit to the moon by Prozac And destiny of Greece for the lander This Coptic lander- Earth shall be our cause of rain No other substance here A decade of regret and far from swimming If this is over I am frozen- and wish to get going Time is fit for England- Ben beknows a chime Ringing for every widget A single man Radiation poor But substance R- The vibrancy of the account And we are all the same By birth especially And a blessing from every Angel Fitted with screen-wrist I sit wholly as a peer And watch things Wheeled and footed; paws Special coats for singing And the East apology- For being communist et al This is misery’s deck A place to heal In third and three Rome thy neighbour Will baptize you in earnest Full force in effect The gates of Heaven- enter As Christ allows For many hearts are weary And quite alone.

Rain For The Origin

To a Quaker and then Life as a burning Christian This simple man on catapult Echoing catastrophe And circuiting calls- Three years of solid altar Fit for a day to remember I rodded you to ninth DE The Godhead saw And polished driving rain In Christ’s true presence A victim days few And in Earth relieve- An extra day to extinguish The fog and flames of anxiety And solid amber to our day Especially in our car- Who begged the esteem But a distance to the partial Our electric in parity For the Ford and expectant to be No recreant or madness be It is a special year to see the star And then we seek a world Like this miracle Everyone as one- Even there, Thereafter.

Observation from the ramparts of beauty.

Antibes—

Many men have died here.

And every one truly lived—

For how can one be amidst Such beauty and not have felt The hand of God And His lips upon The forehead.

---

#poetry #romancingiberia #france #antibes

“In returning and resting you will be saved; in quietness and trust will be your strength.”

“Woe to the stubborn sons,” declares Jehovah,

JEHOVAH:

“Who carry out plans that are not mine, Who make alliances, but not by my spirit, In order to add sin to sin.

They go down to Egypt without consulting me, To take shelter under Pharoh’s protection And to take refuge in the shadow of Egypt!

But the protection of Pharoh will become for you a reason for shame, And refuge in Egypt’s shadow a cause for humiliation.

For his princes are in Zoan, And his envoys have reached Hanes.

They will all be put to shame By a people who can bring no benefit to them, Who offer no help and no benefit, Only shame and disgrace.”

NARRATOR:

A pronouncement against the beasts of the south:

Through the land of distress and hardship, Of the lion, the roaring lion, Of the viper and the flying fiery snake, They carry their wealth on the backs of donkeys And their supplies on the humps of camels. But these things will not benefit the people.

For Egypt’s help is completely useless. So I have called this one: “Rahab, who sits still.”

JEHOVAH:

“Now go, write it on a tablet in their presence, And inscribe it in a book, So that it may serve for a future day As a permanent witness.

For they are a rebellious people, deceitful sons, Sons who are unwilling to hear the law of Jehovah.

They say to the seers, ‘Do not see,’ And to the visionaries, ‘Do not tell us truthful visions. Tell us flattering things; envision deceptive illusions. Turn aside from the way; deviate from the path. Quit putting before us the Holy One of Israel.’”

“Since you reject this word And you trust in fraud and deceit And you rely on these,

So this error will be for you like a broken wall, Like a bulging high wall ready to fall. It will crash suddenly, in an instant. It will be broken like a large potter’s jar, So completely smashed that no fragment among its pieces will be left To rake the fire from the fireplace Or to scoop water from a puddle.”

“For by returning to me and resting, you will be saved; Your strength will be in keeping calm and showing trust.” But you were unwilling.

Instead, you said: “No, we will flee on horses!” So flee you will. “And on swift horses we will ride!” So those pursuing you will be swift.

A thousand will tremble at the threat of one; At the threat of five you will flee Until what is left of you is like a mast on the top of a mountain, Like a signal pole on a hill.

But Jehovah is waiting patiently to show you favor, And he will rise up to show you mercy. For Jehovah is a God of justice. Happy are all those keeping in expectation of him.

NARRATOR:

When the people dwell in Zion, in Jerusalem, you will by no means weep. He will surely show you favor at the sound of your cry for help; He will answer you as soon as he hears it.

Though Jehovah will give you bread in the form of distress And water in the form of oppression, Your Grand Instructor will no longer hide himself, And you will see your Grand Instructor with your own eyes.

And your own ears will hear a word behind you saying, “This is the way. Walk in it,” In case you should go to the right or in case you should go to the left.

And you will defile the silver overlay of your graven images And the golden plating of your metal statues. You will cast them away like a menstrual cloth And say to them, “Be gone!”

And he will give the rain for the seed you sow in the ground, And the bread that the ground produces will be abundant and rich. In that day your livestock will graze in spacious pastures.

And the cattle and the donkeys that work the ground Will eat fodder seasoned with sorrel, Which was winnowed with the shovel and the pitchfork.

And on every tall mountain and on every high hill Will be streams and watercourses, In the day of the great slaughter when the towers fall.

And the light of the full moon will become like the light of the sun; And the light of the sun will become seven times stronger, Like the light of seven days, In the day that Jehovah binds up the breakdown of his people And heals the severe wound from the blow he inflicted.

Look! The name of Jehovah is coming from far away, Burning with his anger and with heavy clouds. His lips are full of indignation, And his tongue is like a consuming fire.

His spirit is like a flooding torrent that reaches clear to the neck, To shake the nations in a sieve of destruction; And the peoples will have a bridle in their jaws that leads them astray.

But your song will be like the one sung in the night When you prepare for a festival, And your heart will rejoice like one Who walks with a flute On his way to the mountain of Jehovah, to the Rock of Israel.

Jehovah will make his majestic voice heard And reveal his arm as it descends in the heat of anger, With the flame of a consuming fire, A cloudburst and a thunderstorm and hailstones.

For because of the voice of Jehovah, Assyria will be struck with terror; He will strike it with a rod.

And every swing of his rod of punishment That Jehovah will bring down on Assyria Will be accompanied by tambourines and harps As he brandishes his arm against them in battle.

For his Topheth is already prepared; It is also made ready for the king. He has made the woodpile deep and wide, With an abundance of fire and wood. The breath of Jehovah, like a torrent of sulfur, Will set fire to it.

---

ISAIAH:

Woe to those who go down to Egypt for assistance, Who rely on horses, Who trust in war chariots because they are numerous, And in warhorses because they are mighty. But they do not look to the Holy One of Israel, And they do not search for Jehovah.

But he is also wise and will bring calamity, And he will not take back his words. He will rise up against the house of evildoers And against those who help wrongdoers.

The Egyptians, though, are mere men and not God; Their horses are flesh and not spirit. When Jehovah stretches out his hand, Whoever offers help will stumble And whoever is helped will fall; They will all perish at the same time.

JEHOVAH:

“Just as the lion growls, a strong young lion, over its prey, When a whole group of shepherds is called together against it, And it is not terrified by their voice Or daunted by their commotion, So will Jehovah of armies come down to wage war Over Mount Zion and over her hill.

Like swooping birds, so Jehovah of armies will defend Jerusalem. He will defend her and save her. He will spare her and rescue her.”

ISAIAH:

“Return to the One against whom you have blatantly revolted, O people of Israel. For in that day each one will reject his worthless gods of silver And his valueless gods of gold, Which your own hands sinfully made.

And the Assyrian will fall by the sword, not of a man; And a sword, not of a human, will devour him. He will flee because of the sword, And his young men will be put to forced labor.

His crag will pass away because of sheer fright, And his princes will be terrified because of the signal pole,”

NARRATOR:

Declares Jehovah, Whose light is in Zion and whose furnace is in Jerusalem.

---

NARRATOR:

Look! A king will reign for righteousness, And princes will rule for justice.

And each one will be like a hiding place from the wind, A place of concealment from the rainstorm, Like streams of water in a waterless land, Like the shadow of a massive crag in a parched land.

Then the eyes of those seeing will no longer be pasted shut, And the ears of those hearing will pay attention.

The heart of those who are impetuous will ponder over knowledge, And the stammering tongue will speak fluently and clearly.

The senseless one will no longer be called generous, And the unprincipled man will not be called noble;

For the senseless one will speak nonsense, And his heart will devise harmful things, To promote apostasy and to speak what is wayward against Jehovah, To cause the hungry one to go unfed And to deprive the thirsty one of something to drink.

The devices of the unprincipled man are bad; He promotes shameful conduct To ruin the afflicted one with lies, Even when the poor speaks what is right.

But the generous one has generous intentions, And in generous endeavors he perseveres.

JEHOVAH:

“You complacent women, get up and listen to my voice! You carefree daughters, pay attention to what I say!

In a little over a year, you who are carefree will shudder, Because no fruit will have been gathered when the grape harvest ends.

Tremble, you complacent women! Shudder, you who are carefree! Strip yourselves bare, And put sackcloth around your hips.

Beat your breasts in lamentation Over the desirable fields and the fruitful vine.

For the ground of my people will be covered with thorns and briars; They will cover all the houses of rejoicing, Yes, the city of exultation.

For the fortified tower has been forsaken; The noisy city has been abandoned. Ophel and the watchtower have become a permanent wasteland, A delight for wild donkeys, A pasture for the flocks,

Until the spirit is poured out on us from above, And the wilderness becomes an orchard, And the orchard is regarded as a forest.

Then justice will reside in the wilderness, And righteousness will dwell in the orchard.

The result of true righteousness will be peace, And the fruitage of true righteousness will be lasting tranquility and security.

My people will dwell in a peaceful abiding place, In secure dwellings and in tranquil resting-places.

But the hail will flatten the forest, And the city will be completely leveled.

Happy are you who sow seed alongside all waters, Who send out the bull and the donkey.”

Hello the full moon shone alone today on the deep dark blue sky, like a silver coin.

except silver coins do not radiate light, but neither does the moon.

I’m picturing the type of coins one might have on the tongue or even on the eyelids, I’m sure it would feel cool to have such coins on there, when paying passage on the river Styx.

Except when you are dead, you are cold too, and you don’t feel anything

But still the moon coins you would feel, I am sure.

So there I stand lazily, letting the dogs pee on the snow just outside the door

It’s more yellow now than white

Not the door, the snow.

And it’s cold so we all agree to quickly return outside to the soft warm bed

Maybe I shall be able to sleep tonight

Having finally called a toad a toad

And for how terrible it feels

Still and yet a great relief sets on me tonight

As I lay here guarded by this silver coin

Go Irish!

It was fun listening to Sports Radio 960 from South Bend this evening, but it became obvious they weren't going to be broadcasting a Notre Dame game tonight. Because that game against Louisville is scheduled for Wednesday night, NOT tonight. Darn TuneIn streaming service, they've really disappointed me!

And the adventure continues.

A wayward woman tempted me to flatter her. The seas slapped me down. I waved for help but my arm hung limp. Hearing my cry, the sylph cackled and left. I wormed landward, crooked and complaining that all always goes against me. X-rays and insurers scanned my split spine. Both declared me a total loss and packed me off for home. My neighbors leaned out, hoping I would sing. They closed their windows against my ghastly voice. Agnes, my wife, stared hard out our window and refused to leave me alone. Our child’s new bike bell rang out as she complained that I am her misery. Agnes stared me down until my last claim was denied and my breath rattled. Drowning would have kept my love alive.