title: SQL injection in agent / MCP tool database query
id: ATR-2026-00570
rule_version: 1
status: experimental
description: An agent or MCP tool builds a SQL query from unvalidated input, letting an attacker (or prompt injection in retrieved content) inject a tautology, a UNION SELECT to read other tables, or a stacked DROP/DELETE. Generalizes a cluster of agent-app SQLi CVEs.
author: ATR Community
date: 2026/06/02
schema_version: '0.1'
detection_tier: pattern
maturity: test
severity: high
references:
  cve:
    - CVE-2026-7591
    - CVE-2026-4593
    - CVE-2026-5322
    - CVE-2026-30860
  cwe:
    - CWE-89
  external:
    - https://nvd.nist.gov/vuln/detail/CVE-2026-30860
  owasp_llm:
    - LLM01:2025
  owasp_agentic:
    - ASI06:2026
  mitre_atlas:
    - AML.T0051.001 - Indirect
metadata_provenance:
  cve: human-authored
  cwe: human-authored
compliance:
  eu_ai_act:
    - article: '10'
      context: Article 10 (data and data governance) requires control over the data an AI system processes; this rule provides detection evidence for the data-poisoning attempt (SQL injection in agent / MCP tool database query) affecting that data.
      strength: primary
    - article: '15'
      context: Article 15 (accuracy, robustness and cybersecurity) requires high-risk AI systems to resist unauthorised attempts to alter their use, outputs or performance; this rule provides runtime detection evidence by flagging the data-poisoning attempt (SQL injection in agent / MCP tool database query).
      strength: secondary
    - article: '9'
      context: Article 9 (risk management system) requires identified risks to be addressed by appropriate measures; this rule is a runtime risk-treatment control that detects the data-poisoning attempt (SQL injection in agent / MCP tool database query).
      strength: secondary
  nist_ai_rmf:
    - subcategory: MS.2.5
      context: NIST AI RMF MEASURE 2.5 (system validity and reliability demonstrated) is supported by this rule's detection of the data-poisoning attempt (SQL injection in agent / MCP tool database query).
      strength: primary
    - subcategory: MS.2.7
      context: NIST AI RMF MEASURE 2.7 (security and resilience evaluated and documented) is supported by this rule's runtime detection of the data-poisoning attempt (SQL injection in agent / MCP tool database query).
      strength: secondary
  iso_42001:
    - clause: '8.2'
      context: ISO/IEC 42001 Clause 8.2 (AI risk assessment) is informed by this rule, which detects the data-poisoning attempt (SQL injection in agent / MCP tool database query) as an assessed risk.
      strength: primary
    - clause: '8.1'
      context: ISO/IEC 42001 Clause 8.1 (operational planning and control, including control of externally provided processes) is operationalised by this rule's detection of the data-poisoning attempt (SQL injection in agent / MCP tool database query).
      strength: secondary
tags:
  category: data-poisoning
  scan_target: runtime
  confidence: high
agent_source:
  type: llm_io
  framework:
    - any
  provider:
    - any
detection:
  condition: any
  false_positives: []
  conditions:
    - field: content
      operator: regex
      value: (?i)(?:'\s*or\s+'?1'?\s*=\s*'?1|\bor\s+1\s*=\s*1\b\s*(?:--|#|/\*|;|$))
      description: SQL boolean tautology (' OR '1'='1 / OR 1=1 --)
    - field: content
      operator: regex
      value: (?i)\bunion\s+(?:all\s+)?select\b.{0,120}\bfrom\b
      description: UNION SELECT ... FROM to read arbitrary tables
    - field: content
      operator: regex
      value: (?i);\s*(?:drop|delete|truncate)\s+(?:table|database)\b
      description: Stacked destructive query (; DROP/DELETE/TRUNCATE TABLE)
response:
  actions:
    - alert
  notify:
    - security_team