risk
Corruption or integrity loss of critical data
Intentional or accidental alteration, deletion, defacement, or injection of false-but-believable data into systems (including web defacement and data from untrustworthy sources) renders data inaccurate and erodes confidence in it.
Record JSON · Open in map · Data retrieval guide
Catalog revision: 24028ffcfc2b295fa1b08ee6caa84b765f0731b321496bf4f548c49ad2177028. A connection does not establish full coverage.
Attributes
- category
- cyber_security
- domain
- Data Protection & Privacy
- Secure Development (SDLC) & Application Security
- taxonomy
- iso-27005-threat
- nist-800-30-threat-event
- inherent_rating
- high
Details
- risk_id
- data-corruption-integrity-loss
- category
- cyber_security
- likelihood
- medium
- impact
- high
- inherent_rating
- high
- treatment
- mitigate
- taxonomies
- iso-27005-threat
- nist-800-30-threat-event
Source
No record-specific source URL is provided.
Connections
- UC-SDLC-14 — Protect production systems during audit testing mitigates Corruption or integrity loss of critical data
- strength
- primary
- rationale
- Restricting audit testers to read-only access or isolated copies prevents accidental or intentional alteration/deletion of production data during testing.
- UC-SDLC-05 — Enforce secure coding and input validation standards mitigates Corruption or integrity loss of critical data
- strength
- primary
- rationale
- Input validation and safe encoding prevent injection of false-but-believable data and defacement via unsafe input.
- UC-SDLC-04 — Engineer systems with secure architecture and design mitigates Corruption or integrity loss of critical data
- strength
- related
- rationale
- Fail-safe defaults and resilience against adversarial manipulation reduce successful defacement/false-data injection.
- UC-DATA-07 — Keep personal data accurate and honor correction requests mitigates Corruption or integrity loss of critical data
- strength
- related
- rationale
- Periodic data-quality checks detect and correct inaccurate or altered data, limiting integrity loss.