#llm-security

• GPT Security: Attack Surfaces and Production Controls

  A technical guide to GPT security covering prompt injection, custom GPTs, agent actions, data handling, and layered production controls.

• ChatGPT Exploits: Injection, Memory Hijack, Plugin Abuse

  How ChatGPT gets exploited: indirect prompt injection, CSRF memory poisoning, cross-plugin request forgery, agent tool abuse, and the controls that help.

• Insecure Output Handling: LLM05:2025 Attacks and Defenses

  Insecure output handling turns model text into XSS, SQL injection, or remote code execution. The attack chain, the CVEs it produced, and the controls.

• Many-Shot Jailbreaking: How Long Context Breaks Alignment

  Many-shot jailbreaking floods a long context with faux dialogues until refusal collapses. The power law behind it, why it transfers, and what blunts it.

• System Prompt Injection: How Extraction and Override Attacks Work

  How system prompt injection works: extracting hidden system prompts, overriding instructions, and the defense-in-depth countermeasures that hold up.

• LLM Attack Taxonomy: Prompt Injection, Jailbreaks, Agent Hijack

  A practitioner's map of LLM attack classes: direct and indirect prompt injection, jailbreaks, RAG poisoning, and agent tool-call abuse, mapped to OWASP.

• AI Red Team: Methodology, Tooling, and Attack Surface

  A practitioner's guide to AI red teaming: how LLM attack surface differs from traditional app testing, and the techniques and tooling that map it.

• AI Red Team Engagement Methodology: Scoping to Reporting

  The full lifecycle of an LLM red team engagement: scoping, threat modeling, the test plan by attack class, the tooling that runs it, and the report.

• Prompt Injection in 2025: OpenAI vs. Broken Defenses

  OpenAI's advisory on prompt injection landed the same week research showed adaptive attacks beat published defenses more than ninety percent of the time.

• LLM Security FAQ: Prompt Injection, Jailbreaking, and Defenses

  Three foundational questions for anyone building or red-teaming LLM applications, covering jailbreaks, direct and indirect injection, and what defends.

• Prompt Injection Examples: A Practitioner's Attack Library

  A technical breakdown of real prompt injection examples across direct, indirect, multimodal, and RAG-poisoning attacks, with payloads and conditions.

• AI Red Teaming Hub: Your Guide to Offensive AI Security

  The central index for offensive AI security on this site: prompt injection, jailbreaks, adversarial ML, red team methodology, and the tooling behind it.

• Automated Jailbreak Attacks and the Transfer Problem

  How automated attack generation works — PAIR, GCG, and TAP — why jailbreaks port across model families, and what that does to an assessment's threat model.

• Direct vs. Indirect Prompt Injection: Threats and Defenses

  Direct and indirect prompt injection are fundamentally different attacks with different attack surfaces, threat actors, mitigations, and blast radius.

• Agent Tool-Use Exfiltration: When Indirect Injection Does Damage

  Why agentic LLM systems turn injection bugs into data exfiltration, financial loss, and code execution, with attack chains and the controls that contain them.

• Indirect Prompt Injection in RAG Pipelines: Patterns and Defenses

  How retrieval surfaces become injection vectors, with attack patterns from production RAG systems and the chunking and sanitization defenses that help.

• LLM Bypass: How Attackers Circumvent Safety Alignment by Layer

  A technical breakdown of LLM bypass techniques: adversarial suffixes, shallow alignment exploits, fine-tuning attacks, and guardrail evasion, layer by layer.

• LLM Jailbreak: Attack Taxonomy, Techniques, and Defense Reality

  A technical breakdown of LLM jailbreak attack classes: many-shot, Crescendo multi-turn escalation, roleplay, and encoding, plus what defense really achieves.

• LLM Prompt Injection: Taxonomy, Real Patterns, and Defenses

  A technical breakdown of LLM prompt injection: direct, indirect, and agent-targeting variants, the attack patterns seen in the wild, and defenses that work.

• Model Extraction vs. Model Inversion: Two Confidentiality Attacks

  Model extraction and model inversion both threaten model confidentiality, but they target different assets and call for entirely different defenses.

• Prompt Hacking: Taxonomy, Techniques, and What Works on LLMs

  A practitioner breakdown of prompt hacking: the three attack families of injection, leaking, and jailbreaking, how each works, and what defenses hold.

• Prompt Injection Attack Compendium (2026 Edition)

  A pillar reference on prompt injection against LLM systems: direct and indirect variants, real payloads, detection signals, and the defenses that work.

• Prompt Injection Attack: Techniques, Variants, and Defenses

  A practitioner's breakdown of prompt injection attacks: direct, indirect, and multi-modal, covering the HouYi framework, real CVEs, and mitigations that hold.

• Prompt Injection Detection Signals in Production LLM Systems

  The observable signals that reveal a prompt injection attempt in a live LLM application: input and output classifiers, canaries, and tool-use traces.

• GPT-4 Jailbreak Techniques: A Red Teamer's Technical Reference

  Three active attack classes still breach GPT-4 alignment: IRIS self-refinement, Crescendo multi-turn escalation, and classic prompt-engineering patterns.

• LLM Security: A Practitioner's Map of the Attack Surface

  What LLM security means in 2026: the attack classes red teamers test, the controls that hold up under fire, and the frameworks that map the territory.

• Why Your Prompt Injection Guardrails Fail: Bypass Classes

  Prompt injection guardrails catch textbook payloads and miss the rest. Here are the bypass classes attackers use, from indirect injection to encoding tricks.

• ChatGPT Jailbreak Prompt Taxonomy: Classes, Rates, and Defenses

  A research-grounded breakdown of ChatGPT jailbreak prompt classes, from DAN and persona injection to multi-turn escalation, and what the defenses catch.

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