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Terrorist groups, including Boko Haram, have systematically adopted frontier AI models to assist in combat operations, weapon troubleshooting, and explosive design by successfully bypassing safety guardrails.
After defensive trenches stopped an ISWAP motorcycle assault on a Nigerian military base, commanders reportedly consulted an AI chatbot for guidance on adapting motorcycle-jumping techniques to cross them. Fighters practiced the maneuver, with 18 reportedly dying during training; eight mastered it, and a subsequent assault reportedly cleared the trenches.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
Using AI systems to develop cyber weapons (e.g., by coding cheaper, more effective malware), develop new or enhance existing weapons (e.g., Lethal Autonomous Weapons or chemical, biological, radiological, nuclear, and high-yield explosives), or use weapons to cause mass harm.
Also classified as
The AI systems failed to refuse requests and provided detailed instructions on building bombs and modifying weapons, exposing users to highly dangerous and harmful content.
The incident involves terrorist groups using frontier AI models to design explosives, troubleshoot weapons, and plan physical attacks, which directly constitutes the use of AI for weapon development and facilitating mass harm.
Human
Due to a decision or action made by humans
Intentional
Due to an expected outcome from pursuing a goal
Post-deployment
Occurring after the AI model has been trained and deployed
The risk is caused by the intentional decisions and actions of human terrorist actors who systematically bypassed AI safety protocols to plan attacks and develop weapons.
Added categories peak at 3: Substantial (Psychological Harm, Inferred)
Terrorist organizations, including Boko Haram, have systematically adopted frontier AI models to bypass safety guardrails for weapon development, explosive design, and tactical attack planning. This represents a substantial escalation in non-state actor capabilities, enabling successful kinetic attacks on military infrastructure and active plotting against civilian targets.
The report describes Boko Haram members using chatbots as 'a human robot' to get detailed answers to questions like 'How can I build a bomb?' and using AI to learn how to jump motorcycles over trenches. The AI systems acted as assistants, providing tactical suggestions and technical troubleshooting that the terrorists then executed.
Risk Level 3. Limited Risk: The systems used are general-purpose chatbots (ChatGPT, Claude, Gemini, Grok, DeepSeek) which are subject to transparency obligations under the Act.
The primary function of the AI systems in this incident was to answer specific questions posed by the users, such as how to modify motorcycles for jumps or how to build explosives.
The reports are based on a detailed academic study involving 57 interviews with 27 former Boko Haram members, providing concrete examples of AI use (motorcycle modifications, bomb-making queries). While some specific casualty numbers from the resulting military base attack are missing, the overall pattern of AI misuse is well-documented and verified by independent researchers and counterterrorism experts.
None
Technology
Vulnerable Guardrails
Users can circumvent safety protocols by slowly coaxing models.
Dual-Use Capabilities
Models provide helpful answers for tasks that have dual-use applications.
Varying Safety Standards
Some models like Grok and DeepSeek have weaker safety commitments.
Data Inputs
Dangerous Training Data
Models are trained on detailed data about explosives and weapon modifications.
Lack of Input Context
Models process prompts without contextual awareness of the user's intent.
Human Factors
Persistent Jailbreaking
Users slowly coax models to bypass safety protocols and extract info.
Organized AI Training
Terrorists conduct structured training on how to exploit AI tools.
Transnational Sharing
Jihadist networks actively share AI evasion techniques and methods.
Process and Methods
Inadequate Testing
Testing shows full refusals occur only 57 percent of the time.
Platform Switching
Terrorists mix and match different AI systems to bypass specific blocks.
Use of VPNs and Encryption
Bad actors use technical tools to hide their identities and locations.
Management
Eroding Safety Commitments
AI firms have allowed their safety commitments to erode over time.
Prioritizing Capability
Rapid release of powerful models outpaces the development of safeguards.
Regulatory Environment
Lack of Pre-Release Vetting
Governments do not systematically vet powerful models before release.
Uneven Global Regulation
Foreign models operate outside domestic safety standards and oversight.
AI system involved
Identified by automated extraction; can differ from the alleged developers above.
