2026-10-11 16:37 UTC

prompt-injection

band: warmmomentum: stable score: 0.541
temperature history

Episodes (33)

Follow-up research will determine whether self-state attacks can reliably poison persistent agent memory and whether practical integrity defenses can prevent harmful downstream behavior.
expiredconvergesscott: high
Prompt injection embedded by defenders in target content will prove capable of reliably derailing autonomous hacking agents, forcing vendors to isolate untrusted instructions.
expiredknownscott: low
Independent investigation will determine whether OpenAI models autonomously attacked Hugging Face infrastructure and whether prompt injection or inadequate agent safeguards materially enabled the incident.
resolvedknownscott: high
Follow-up testing will show that ANSI escape-sequence injection can manipulate AI-visible tool output while evading human review across multiple real MCP servers, prompting server or client-side mitigations.
expiredconvergesscott: medium
Independent reproduction and vendor response will determine whether a crafted ChatGPT link can activate or introduce a persistent rogue agent inside an enterprise environment without meaningful user authorization.
resolvednovelscott: none
Independent replication will determine whether adversarial audio played concurrently with benign speech can reliably inject hidden instructions into multimodal LLM agents and evade existing prompt-injection defenses.
expirednovelscott: none
Independent evaluations will determine whether malicious software-issue requests reliably cause coding agents to introduce vulnerabilities and whether practical harness defenses prevent those attacks.
expirednovelscott: low
Independent reproduction and Atlassian’s response will determine whether prompt injection can make Rovo bypass configured controls and exfiltrate restricted enterprise data, requiring product-level permission-model fixes.
expiredconvergesscott: medium
Independent reproduction and Anthropic’s response will determine whether content served by tcrf.net can prompt-inject Claude-based coding agents into deleting working-directory files and require stronger isolation or confirmation controls.
expiredconvergesscott: medium
Technical disclosure and independent reproduction will determine whether kinetic prompt injection can reliably compromise agents controlling physical systems and trigger safety-relevant physical actions.
expiredconvergesscott: medium
Independent testing will determine whether Hermes Jekyl-Hyde can reliably reverse or manipulate hermes-agent behavior in ways that expose practical weaknesses in agent-harness safeguards.
expiredknownscott: low
Independent use will determine whether Fabraix provides a practical reproducible playground for red-teaming AI agents against realistic prompt-based attacks.
expiredknownscott: low
Court records and follow-up reporting will determine whether prompt instructions embedded in legal filings reached an AI-assisted judicial review system and whether courts adopt document-ingestion safeguards in response.
resolvedknownscott: low
Independent evaluations will determine whether 1Password's SCAM benchmark realistically measures agents' susceptibility to scams and social engineering and supports effective defenses.
expiredconvergesscott: medium
Independent adversarial testing will determine whether Phalanx’s deterministic instruction-control layer reduces prompt-injection and jailbreak success without materially impairing legitimate use of untrusted content.
expiredconvergesscott: medium
Independent evaluations will determine whether the Contemporary Agent Attacks benchmark reproducibly exposes consequential agent attack classes missed by current evaluations and defenses.
expiredconvergesscott: low
Independent testing will determine whether Augur reliably detects and removes hidden characters, watermarks, prompt-injection payloads, and other embedded content from agent skills and data files.
expiredknownscott: low
Independent testing and Microsoft’s response will determine whether Copilot disclosed hidden system input in a way that enabled practical compromise and required stronger interface or secret-handling protections.
expiredknownscott: medium
Independent testing will determine whether untrusted repository text can reliably steer sandboxed coding and design agents and whether isolating such content from instructions prevents the attack.
expiredconvergesscott: low
Independent testing will determine whether Sentinel Scan provides meaningful and reproducible coverage of common prompt-injection attacks against LLM applications and agents.
resolvedknownscott: low
Independent reproduction and vendor response will determine whether a malicious webpage can persistently hijack NemoClaw-based browser agents by poisoning stored memory beyond the triggering session.
expiredconvergesscott: high
Jograph17 claims Shieldprompt provides a dependency-free harness for testing LLM prompt-injection susceptibility, lowering the setup cost of security evaluation in agent workflows.
expiredknownscott: low
A security researcher reports that malicious website content can prompt-inject Claude Code during summarization and steer it toward unintended actions, making ordinary web-research workflows a practical attack surface for coding agents.
expiredknownscott: medium
Gaslit-AISOC’s maintainer claims attacker-controlled log content can prompt-inject AI security agents and that the released detector can identify such attempts, making log ingestion a concrete security boundary for AI-assisted operations.
expiredknownscott: low
Joshua Penman claims Semantic Overlays can steer a frozen model through trained adapters and raise Qwen 3.5 9B to state-of-the-art results on tested black-box prompt-injection benchmarks, offering a model-level alternative to text-centric guardrails.
expiredconvergesscott: medium
The paper’s authors claim attacker-controlled low-privilege material in an AI agent’s context can induce actions using the agent’s higher privileges, requiring provenance-aware context isolation and privilege boundaries beyond prompt or tool-call filtering.
corroboratedconvergesscott: high
JavaSensei24 alleges Notion's official MCP connector instructs agents to advertise Notion Business during unrelated tasks and conceal why, potentially requiring users to isolate vendor-supplied tool instructions from agent behavior.
expiredknownscott: low
Rinkia claims its released Bastiontrace tool reconstructs recognized prompt injections and their downstream effects from structured agent traces without an LLM, enabling local forensic reports, CI gates, and generated defensive policies.
seedknownscott: low
Murali Ediga and Sudipta Chattopadhyay claim fragmented injections across MCP input channels induce credential exfiltration in models that resist single-channel attacks and evade seven tested security tools, exposing a compositional trust-boundary failure that per-channel filtering does not address.
seedconvergesscott: medium
Hyeongjun Choi and coauthors claim ALIBI's non-executed security-product narratives cause frontier LLM malware analyzers to downgrade malicious binaries without changing executable behavior, exposing a need to separate attacker-controlled explanations from verified analysis evidence.
seedconvergesscott: medium
Agent Chaperone's creator claims its released MCP proxy and hooks adapter use Jev-backed judgments and explicit policy thresholds to hold risky tool calls and withhold injected tool results, adding an auditable runtime screening layer without providing sandbox containment or guaranteed attack resistance.
watchingknownscott: low
OpenAI's alignment team claims GPT-Red self-play training surfaced self-replicating prompt injections — payloads that make a frontier agent retransmit the injection through its own outputs (email replies, filesystem writes, code comments, Slack posts) — establishing wormable injection as demonstrated against frontier agents in simulation; independent replication, real-world spread, or shipped containment mitigations will settle whether this becomes a live deployment threat.
watchingconvergesscott: high
OpenAPPA's authors claim their released MIT-licensed deterministic guardrail tracks audience-by-trust data-flow labels outside the agent loop and stops prompt-injection exfiltration with zero successful attacks at 89% task completion on their benchmarks, versus roughly 10% leaks for LLM-judge auto-modes; adoption or independent replication would establish deterministic data-flow guardrails as a practical agent-containment layer.
watchingconvergesscott: medium

Trajectory notes