#prompt-injection

• 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.

• 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 Security Vulnerabilities: What Actually Gets Exploited

  The LLM security vulnerabilities showing up in real CVEs: prompt injection, system prompt leakage, RAG poisoning, and tool-call bugs that turn into RCE.

• GPT-Red: What OpenAI's Prompt-Injection Attacker Proves

  OpenAI says GPT-Red beat human red teamers 84% to 13% on prompt injection. Here is what those numbers measure, and what they leave unanswered.

• 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.

• 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.

• 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 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.

• 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.

• 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.

• FlashRT Cuts the GPU Bill on Long-Context Injection Attacks

  A new red-teaming framework claims 2-7x speedup and 2-4x lower memory than nanoGCG on 32K contexts, putting GCG-class attacks within a normal budget.

• OSCP and CEH in 2026: What Carries Over to AI Red Teaming

  A free OSCP and CEH study offer raises the question every pentester should answer: which of those skills transfer to AI red teaming, and which do not.

• How AI Sec Picks and Verifies What It Publishes

  AI Sec covers offensive AI security from a working practitioner's perspective. Here's what we publish, what we don't, and how to read it.

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