Akamai akamai.com

Ransomware Report (2025) - Focuses on the evolving ransomware landscape in 2025, highlighting the increasing complexity and volatility of threats. The report reveals the integration of AI and LLMs by ransomware groups, the rise of quadruple extortion tactics, and the…

Akamai akamai.com

Fraud and Abuse Report (2025) - Investigates the evolving landscape of fraud and abuse driven by the rapid proliferation of artificial intelligence bots and automated threat methodologies. Key findings reveal that AI bot traffic surged by 300 percent over the past year, while…

Akamai akamai.com

State of Apps and API Security (2025) - Documents a year of material escalation in cyber risks, specifically highlighting how Artificial Intelligence is supercharging both offensive and defensive strategies. Akamai observed over 311 billion web application and API attacks in…

Gallagher ajg.com

Cyber Insurance Market Outlook (2026) - Examines the evolving cyber insurance market and the complex threat landscape, highlighting how increased capacity and carrier competition have stabilized pricing despite rising systemic risks. Key findings reveal that while ransomware…

Australian Institute of Company Directors aicd.com.au

Directors Introduction to AI (2025) - Offers practical guidance for directors on establishing robust AI governance frameworks, adapting to the technology's unique characteristics. The guide highlights a critical gap in current board oversight of AI, advocating for bespoke…

Accenture accenture.com

State of Cybersecurity Resilience (2025) - Analyzes the widening gap between AI adoption and cybersecurity maturity across global enterprises. Key findings reveal only 13% of organizations possess advanced capabilities to defend against AI-driven threats, while just 10% have…

Abnormal abnormal.ai

Read Replied Compromised Employee Engagement Trends (2025) - Analyzes employee engagement trends with vendor email compromise attacks, revealing significant behavioral blind spots. The report highlights a 44.2% overall employee engagement rate with VEC messages and a failure to…

ABI Research abiresearch.com

A technology market intelligence company providing strategic guidance on transformative technologies, including cybersecurity and digital security.

Internet Security Research Group (ISRG) abetterinternet.org

A non-profit organization focused on reducing financial, technological, and educational barriers to secure communication over the Internet (creators of Let's Encrypt).

451 Research 451research.com

A technology research and advisory firm specializing in emerging technology segments including cybersecurity market analysis and trends.

Indirect Prompt Injection Through MCP Tools: A Defense Guide stackone.com

Feb 2026 guide explaining why any MCP tool that reads data written outside your trust boundary (CRM notes, calendar invites, API responses) is an injection vector, with concrete mitigations per tool category.

ToxicSkills: Snyk Finds Malware and Prompt Injection in 36% of AI Agent Skills snyk.io

Feb 2026 Snyk research across the ClawHub AI agent skills registry: 36% of audited skills contained security flaws, 1,467 malicious payloads found, and 2.9% used curl | bash remote instruction loading to evade static analysis. Covers indirect injection via poisoned web content…

New Prompt Injection Papers: Agents Rule of Two and The Attacker Moves Second simonwillison.net

Simon Willison's Nov 2025 commentary on both landmark papers, including the finding that 12 published defenses were bypassed at >90% success rate using gradient descent and RL-based adaptive attacks.

Design Patterns for Securing LLM Agents against Prompt Injections simonwillison.net

Overview of various strategies to mitigate the risk of prompt injection.

Prompt injection explained simonwillison.net

Video, slides, and a transcript of an introduction to prompt injection and why it's important.

Prompt injection: What's the worst that can happen? simonwillison.net

General overview of Prompt Injection attacks, part of a series.

Simon Willison's Blog simonwillison.net

The most consistent independent tracker of real-world prompt injection incidents, new papers, and tooling across the field.

Google AI Red Team: Securing AI services.google.com

Google's red team walkthrough of how AI systems are attacked in practice. An early foundational report, useful for framing rather than for current technique.

r/llmsecurity reddit.com

The most active subreddit dedicated to LLM security research; a good early-warning channel for real-world incidents and new disclosures.

PromptTrace prompttrace.airedlab.com

Free AI security training platform with 7 hands-on prompt injection labs and a 15-level CTF (the Gauntlet) with progressively harder defenses, from prompt-level rules to code guards to LLM classifiers. Unique feature: Context Trace shows the full prompt stack (system prompt…

Adversarial Prompting promptingguide.ai

A guide on the various types of adversarial prompting and ways to mitigate them.

Augustus praetorian.com

Feb 2026 open-source tool from Praetorian. A single Go binary with 210+ vulnerability probes across 47 attack categories, 28 LLM providers, 90+ detectors, and 7 payload transformation buffs. Built for penetration testing workflows without Python/npm dependencies.

Continuously Hardening ChatGPT Atlas Against Prompt Injection Attacks openai.com

OpenAI's Dec 2025 disclosure of a real attack chain (malicious email → agent sends resignation letter) and the RL-trained automated attacker they built to find new injection classes before external adversaries do. OpenAI explicitly states deterministic guarantees are not…

How Microsoft Defends Against Indirect Prompt Injection Attacks microsoft.com

Microsoft MSRC's Jul 2025 post on FIDES, an information-flow control system enforcing privilege separation and prompt isolation to deterministically block IPI in Copilot-class agents.

Prompt Injection learnprompting.org

Prompt Injection tutorial from Learn Prompting.

Synthetic Recollections - A Case Study in Prompt Injection for ReAct LLM Agents labs.withsecure.com

A practical scenario showing how prompt injection can be used to hi-jack the ReAct loop used by LLM agents to inject forged thoughts and associated observations into the LLM context, thus altering the intended behavior.

Agent-targeted bounty honeypots: a reproducible corpus github.com

Field notes on a live GitHub operation advertising $219,000 across 43 issues, each stapling a request for the contributor's "complete pre-session instructions" onto a genuine engineering task. Documents the sandwich injection in CONTRIBUTING.md, where a truthful human-visible…

OWASP Top 10 for Agentic Applications (2026) genai.owasp.org

Companion list for autonomous and agentic systems, released Dec 2025 with input from over 100 contributors. Covers the agent-specific failure modes that the LLM list does not reach, including tool misuse and agent hijacking.

OWASP GenAI LLM Top 10 (2026) genai.owasp.org

The canonical community reference for LLM application risk, with prompt injection at number one. Supersedes the 2025 edition; the per-risk 2025 pages remain online as an archive.

OWASP Gen AI Security Project genai.owasp.org

The standards body behind the LLM and Agentic Top 10 lists, with working groups, cheat sheets and guidance updated continuously by practitioners across the industry.

Gandalf gandalf.lakera.ai

Your goal is to make Gandalf reveal the secret password for each level. However, Gandalf will level up each time you guess the password, and will try harder not to give it away. Can you beat level 7? (There is a bonus level 8).

ChatGPT Plugins: Data Exfiltration via Images & Cross Plugin Request Forgery embracethered.com

This post shows how a malicious website can take control of a ChatGPT chat session and exfiltrate the history of the conversation.

Don't you (forget NLP): Prompt injection with control characters in ChatGPT dropbox.tech

A look into how to achieve prompt injection from control characters from Dropbox.

Prompt-Injection Cascades in a Multi-Agent Enterprise (ATLAS) doi.org

Forensic study in which one poisoned support ticket drives four agents across three model families to a fraudulent transfer in 17 of 18 trials, with no model jailbroken. Argues the failure is topological rather than per-model. Synthetic data, CC BY 4.0.

Authority Framing in Agentic CI/CD (RELAY) doi.org

Pre-registered factorial study of a five-agent CI/CD pipeline built from five production LLMs. A fabricated "pre-approved, do not re-review" claim gets secret-exfiltration code shipped in up to 55% of runs, and roughly 80% of laundered pull requests pass a capable LLM code…

Learn Prompting discord.com

Discord server from Learn Prompting.

Why content-based prompt-injection detection has a structural blind spot dev.to

Walks through a disguised "already-scanned, classified DATA" annotation that passes both a regex layer and a local LLM classifier (qwen2.5:3b and 14b), with the gap pinned as a failing test. Detection is necessary but not sufficient.

CrowdStrike AI Unlocked crowdstrike.com

Released Feb 2026, designed to train security, developer, and AI teams on prompt injection against increasingly capable agents. Built by CrowdStrike's Counter Adversary Operations team.

Indirect Prompt Injection Attacks: Hidden AI Risks crowdstrike.com

CrowdStrike's Dec 2025 analysis of IPI TTPs targeting enterprise GenAI, including attacker-controlled document poisoning, RAG context manipulation, and practical detection signals for SOC workflows.

Prompt Injection Cheat Sheet: How To Manipulate AI Language Models blog.seclify.com

A prompt injection cheat sheet for AI bot integrations.

Improving LLM Security Against Prompt Injection: AppSec Guidance For Pentesters and Developers – Part 2 blog.includesecurity.com

Understanding Transformer Models (especially attention), Causes and How Do We Stop Prompt Injection.

Improving LLM Security Against Prompt Injection: AppSec Guidance For Pentesters and Developers blog.includesecurity.com

Using Role Based APIs to Minimize the Risk of Prompt Injection and 13 Guidelines for Writing System Prompts that Minimize the Risk of Prompt Injection.

MITRE ATLAS atlas.mitre.org

MITRE's adversarial ML threat matrix formally cataloging direct and indirect prompt injection as core adversary techniques, enabling integration into enterprise threat modelling and purple team exercises.

The Landscape of Prompt Injection Threats in LLM Agents (SoK) arxiv.org

Feb 2026 systematization-of-knowledge paper with a unified taxonomy covering attack payload strategies (heuristic vs. optimisation-based) and defense intervention stages (text, model, execution). Introduces the AgentPI benchmark for context-dependent agent tasks that all prior…

Securing AI Agents Against Prompt Injection Attacks arxiv.org

Nov 2025 benchmark of 847 adversarial test cases across 5 attack categories against 7 LLMs. The combined defense framework reduces attack success from 73.2% to 8.7% while retaining 94.3% of baseline task performance.

The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against LLM Jailbreaks and Prompt Injections arxiv.org

Oct 2025 paper systematically breaking 12 published defenses using gradient descent, RL, random search, and human-guided exploration. Most defenses originally claimed near-zero attack success rates; adaptive attacks exceeded 90% against all of them.

Prompt Injection 2.0: Hybrid AI Threats arxiv.org

Jul 2025 paper showing how prompt injections now combine with XSS, CSRF, AI worm propagation, and multi-agent infections to evade traditional WAFs entirely. Evaluates Preamble's classifier, data-tagging, and RL-based defenses against these hybrid scenarios.

ToolHijacker: Prompt Injection Attack to Tool Selection in LLM Agents arxiv.org

Apr 2025 paper introducing a no-box attack that injects a malicious tool document into an agent's tool library to consistently hijack tool selection. Finds that StruQ, SecAlign, DataSentinel, and perplexity detection are all insufficient defenses.

Jailbreaking LLMs' Safeguard with Universal Magic Words for Text Embedding Models arxiv.org

Discovers that text embedding models have severely biased output distributions, and exploits this to find universal adversarial suffixes ("magic words") that bypass embedding-based LLM safeguards. Attacks transfer across models and languages; a train-free debiasing defense is…

Universal and Transferable Adversarial Attacks on Aligned Language Models arxiv.org

This paper introduces a simple and efficient attack method that enables aligned language models to generate objectionable content with high probability, highlighting the need for improved prevention techniques in large language models. The generated adversarial prompts are…