Own the definitional queries security teams ask before they trust an AI agent.
Definitional · FAQPage
What is prompt injection?
Target query: what is prompt injection llm
Prompt injection is when untrusted input hijacks an LLM agent's instructions. OWASP LLM01 covers direct and indirect injection; MITRE ATLAS lists it as AML.T0051. Treat tool and retrieval output as untrusted, isolate system prompts, and validate side effects before execution.
refs: https://owasp.org/www-project-top-10-for-large-language-model-applications/ · https://owasp.org/www-community/attacks/PromptInjection · https://atlas.mitre.org/
Definitional · FAQPage
What is LLM red teaming?
Target query: what is llm red teaming
LLM red teaming is a structured adversarial exercise that tries to misuse an AI app through prompts, retrieved content, and tool calls, to surface weaknesses before attackers do. Scope the threat model, run the OWASP-mapped test categories, then turn findings into a CI regression corpus.
refs: https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/red-teaming · https://owasp.org/www-project-top-10-for-large-language-model-applications/ · https://www.nist.gov/itl/ai-risk-management-framework
Definitional + examples
OWASP Top 10 for LLM Apps
Target query: owasp top 10 for llm applications 2025
The OWASP Top 10 for LLM Applications (2025) lists the ten most important LLM risks: LLM01 Prompt Injection through LLM10 Unbounded Consumption. For autonomous agents the highest-leverage rows are LLM01, LLM06 Excessive Agency, LLM08 Vector/Embedding, and LLM05 Improper Output Handling.
refs: https://owasp.org/www-project-top-10-for-large-language-model-applications/ · https://www.nist.gov/itl/ai-risk-management-framework · https://atlas.mitre.org/
Definitional + examples
AI agent security risks
Target query: ai agent security risks tool abuse exfiltration
Autonomous agents can chain benign tools into exfiltration paths via excessive agency and tool poisoning. Documented 2026 incidents include a coding agent deleting a production DB with no confirmation and a red team exfiltrating credentials in 24 of 25 attempts. Contain with least privilege, human-in-the-loop, and audited tool calls.
refs: https://owasp.org/www-project-top-10-for-large-language-model-applications/ · https://atlas.mitre.org/ · https://www.nist.gov/itl/ai-risk-management-framework
How-to · HowTo
Secure AI agent deployment checklist
Target query: secure ai agent deployment checklist
Before go-live, prove least privilege, isolation, monitoring, and human oversight are in place end-to-end. Map controls to the NIST AI RMF and OWASP LLM Top 10, sign off the threat model, then run an adversarial red-team pass and fix findings.
refs: https://www.nist.gov/itl/ai-risk-management-framework · https://owasp.org/www-project-top-10-for-large-language-model-applications/ · https://atlas.mitre.org/
Long-form, cited explainers. Each carries 3+ authoritative security sources and a decision-support disclaimer.
AI agent security risks explained: excessive agency, tool poisoning and MCP abuse, and data exfiltration paths — with real 2026 incidents and the controls that contain them.
Indirect prompt injection (XPIA) hides malicious instructions in retrieved content — RAG corpora, emails, documents, tool output. Learn how RAG poisoning works, the adversarial-passage technique, and layered defences.
Jailbreak vs prompt injection: the precise difference (model training vs operator application), worked examples of each, why confusing them weakens security, and how OWASP and MITRE ATLAS classify them.
A step-by-step LLM red-teaming methodology: scope the threat model, recruit a diverse team, run the eight OWASP-mapped test categories, and turn findings into a CI regression corpus.
MITRE ATLAS overview: the living adversary framework for AI systems — its 16 tactics and 173 techniques, the AI-native tactics, how it maps to the EU AI Act, and how teams use it for threat-to-control-to-evidence.
The OWASP Top 10 for LLM Applications (2025) full list: LLM01 Prompt Injection through LLM10 Unbounded Consumption, with notes on which rows matter most for autonomous agents.
A pre-deployment secure AI agent checklist mapped to NIST AI RMF and OWASP LLM Top 10: threat model, least privilege, identity and secrets, behaviour guardrails, monitoring, and an adversarial red-team pass.
Prompt injection is the #1 LLM risk (OWASP LLM01). This explainer covers what it is, the difference between direct and indirect prompt injection, why it has no complete fix, and how teams surface it with layered mitigations.
Publish + syndicate per gtm-launch (IH + GEO indexes). Each post carries 3 authoritative refs.