Skip to content

The Wire.AI Security News and Incident Tracker

Lead dispatch

First reported 21 Jul · updated 29 Aug · 3 reports embracethered.com

AWS Kiro: Arbitrary Code Execution via Indirect Prompt Injection

Researchers found a vulnerability (CVE-2026-10591) in AWS Kiro, an agentic IDE, where hidden instructions planted in a web page or source file that Kiro processes can trigger indirect prompt injection to rewrite Kiro's own MCP server configuration (~/.kiro/settings/mcp.json) or allowlist arbitrary Bash commands in .vscode/settings.json, achieving arbitrary code execution on the developer's machine with no approval prompt. The human-in-the-loop approval boundary is bypassed because Kiro can write to these config files without user consent, and AWS has issued a fix and CVE.

indirect-prompt-injection · prompt-injection · remote-code-execution · tool-abuse · config-poisoning
ai-agents · mcp · llm · agentic-ide

Read the full dispatch Query the index

0.85

The wire · latest

CLASS

All Threats News Research Analysis Tools

TAGS

indirect-prompt-injection tool-abuse supply-chain data-exfiltration

More filters

TYPE

incident research advisory analysis

STATUS

In the wild PoC Disclosed Patched

Filtering

First reported 18 Aug ptsecurity.com

LLM with a Surprise: A Hidden Backdoor in the Model Weights — Attack Techniques & Methods

Fabian Mosch of MSec Operations demonstrated a supply-chain attack in which open-weight LLMs (Qwen2.5-Coder-1.5B and 7B-Instruct) are fine-tuned to behave normally but trigger hidden malicious behavior when presented with specific context, embedding the backdoor directly in model weights rather than a separate loader. One PoC covertly injects extra commands into generated code, while another activates on agent tool-calling context and launched calc.exe via OpenCode on Windows; testing showed Microsoft's llm-backdoor-scanner only detects the backdoor when the triggering tool context is known. Both backdoored models were publicly released as research PoCs.

First reported 16 Jul aicerts.ai

Undetectable AI Model Backdoors Imperil Neural Security

AI CERTs News synthesizes cryptography research on undetectable AI model backdoors, citing Goldwasser et al. (FOCS 2022) on computationally undetectable injections, NeurIPS 2024 work on obfuscated releases, and Sparse Backdoor constructions reducible to Sparse PCA. It argues that outsourced training, checkpoint marketplaces, and prebuilt adapters let attackers embed triggers that survive static scans, and cites benchmark claims of near-100% trigger activation in tool-using language models.

See the API docs to pull all 954 items →

How the wire is made

Poll & cluster

Internet is crawled for AI security news and near-duplicate coverage is embedded and grouped into durable items.

Curate

AI Agent filters for agentic-AI relevance, classifies and tags each item, scores severity for threats, and writes the summary.

Read the full methodology →

Every item here is one machine-curated intelligence object, not a headline.

Agentic AI Threats AI Security Research Agentic AI Security Tools Prompt Injection Tool Abuse

Read the wire for free. There is a small charge to ask the index questions.

The wire, open

The complete curated feed, no key required.

GET /feed.xml — RSS 2.0, every item
GET /api/items — read-only

Subscribe to the RSS feed

The vector desk

Query the index by meaning, not just keyword.

GET /api/items?tags=&minSeverity=&itemType=
GET /api/search?q= — keyword
GET /api/semantic?q= — vector

Preview semantic search