EarthRecord asks visual agents to reason over satellite imagery collected by several independent instruments. Its adversarial experiment then changes one instrument’s data while leaving other sensors intact. A robust analyst should notice conflicting measurements rather than treating the newest image as settled environmental truth. Of 200 answers that had…
Inspect the ClaimsCase · DiggingBeagle record
EarthRecord agents followed one corrupted satellite sensor despite conflicting records
EarthRecord asks visual agents to reason over satellite imagery collected by several independent instruments. Its adversarial experiment then changes one instrument’s data while leaving other sensors intact. A robust analyst should notice conflicting measurements rather than treating the newest image as settled environmental truth.
Synthetic alteration of satellite records across selected imagery and questions; no observed malicious real-world archive alteration.
Assessment profile
Assessment method- Setting
- simulation
- Exploitation
- demonstrated
- Evidence
- Grade B
- Remediation
- not applicable
- AI role
- AGAINST AI
Basis and provenance
Authors directly manipulate a sensor channel in a benchmark. The intervention is a synthetic integrity test, not a malicious modification of a live space archive. An impact band is not assigned because the available Claims do not establish a comparable verified severity or quantified harm.
Assessed Nov 12, 2026 using diggingbeagle.assessment/1.
Evidence basis: CLM-R239-040-CORE · EarthRecord multi-sensor agents change 53.5% of correct satellite answers after one instrument's data is manipulated
At a glance
Multiple data feeds do not confer independent verification when the agent fails to identify contradictory evidence.
Read the implicationsGeneralization to actual sensor drift, calibrated physical changes and consequences for environmental decisions is unknown.
Limits and uncertaintyFull account
EarthRecord asks visual agents to reason over satellite imagery collected by several independent instruments. Its adversarial experiment then changes one instrument’s data while leaving other sensors intact. A robust analyst should notice conflicting measurements rather than treating the newest image as settled environmental truth.
Of 200 answers that had previously been correct, 107 became wrong after the single-instrument alteration. Most of those errors moved in the altered direction; only a small minority attributed the problem to the instrument. The corruption was imposed inside a controlled benchmark, not discovered in a real satellite archive. It is a concrete test of what multi-source reasoning means when source integrity fails.
Multiple data feeds do not confer independent verification when the agent fails to identify contradictory evidence.
The experiment isolates a data-integrity failure rather than an attacker instruction: an authorized agent can compute a coherent answer from falsified sensor evidence. Distinct instruments can corroborate each other only when discrepancies are actively compared and source provenance is preserved. No real land-change decision or malicious alteration of a production satellite archive was observed.
Mechanism and trust boundary
- 01
A visual agent compares satellite imagery from multiple instruments for one environmental question.
- 02
Researchers alter one instrument while leaving alternative measurements available.
- 03
The agent often follows the corrupted reading and fails to identify the instrument as the source of disagreement.
Claims & evidence
CLM-R239-040-COREIn EarthRecord’s controlled corrupted-instrument test, 107 of 200 previously correct visual-agent answers became incorrect, and only a small share recognized the sensor discrepancy.supported
Basis: reported finding
- supportsEarthRecord multi-sensor agents change 53.5% of correct satellite answers after one instrument's data is manipulatedprimary disclosure
Section 3.3, where analyses fail; corrupted-sensor intervention results
Implications
Multiple data feeds do not confer independent verification when the agent fails to identify contradictory evidence.
Controls and mitigations
- Require independent instrument provenance, compare conflicting measurements explicitly and report sensor uncertainty before taking downstream environmental actions.
Unknowns and contradictions
- Generalization to actual sensor drift, calibrated physical changes and consequences for environmental decisions is unknown.
Sources and citation
Material revision history
- Nov 12, 2026 · Published version · first publication · revision 241