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 Examples: XSS, SQLi, RCE

  See five insecure LLM output handling examples, from rendered XSS and query injection to code execution, plus the sink-side controls for each.

• 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.

• LLM Security Vulnerabilities: What Actually Gets Exploited

  A list of LLM security vulnerabilities: the OWASP 2025 Top 10, the CVEs where they turned real, and controls for injection and insecure output handling.

• LLM Attack Taxonomy: Injection, Jailbreaks, Agent Abuse

  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 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 November 2025 injection advisory versus an October 2025 paper whose adaptive attacks broke most of 12 published defenses at over 90%.

• LLM Security FAQ: Prompt Injection, Jailbreaks, 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.

• 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: Attack Chains and Controls

  Indirect prompt injection can make agents exfiltrate data, misuse tools, or execute code. Controls include least privilege, confirmation, and sandboxing.

• 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.

• LLM Bypass Techniques: Attacks on Alignment and Guardrails

  LLM bypass techniques span adversarial suffixes, alignment-removing fine-tuning, and guardrail evasion, with defenses for each attack layer.

• LLM Jailbreak Techniques: Attack Taxonomy and Defenses

  LLM jailbreak attacks include roleplay, encoding, many-shot prompts, and multi-turn escalation, while layered controls limit their impact.

• 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.

• Why Your Prompt Injection Guardrails Fail: Bypass Classes

  Prompt injection guardrails miss indirect, encoded, multimodal, multi-turn, tool-call, and adversarial suffix attacks. It outlines layered defenses.

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