World-First SEM-based Recovery of Crash EDR Data from the EEPROM of a Severely Damaged SRS Module Using CrashScan
2026-08-12T07:23:25Z•e8ecfca842713d8e9f1fa647d149ff779b35b422e951a5de763678bdb2f79058
IoT intrusion detectionLLM securityMixture-of-ExpertsPrime+ProbeSQL injectionSSRFXSSagentic AIautomotive forensicsbranch predictorscheckpoint poisoningcode executioncommand injectioncryptographic hardwaredenial of servicefault injectionmodel supply chainprompt injectionside-channel attackstool misusewatermark removalweb exploitation
What happened
The document is an arXiv security and reliability research feed containing studies on forensic recovery of automotive crash data, AI-image watermark removal, streaming LLM moderation, LLM-mediated web exploitation, IoT intrusion detection, side-channel-resistant branch prediction, agentic LLM vulnerabilities, malicious MoE model checkpoints that hijack serving load, and fault detection for cryptographic hardware. The most directly actionable security findings concern prompt-injection-mediated web attacks, agent/tool misuse, checkpoint supply-chain poisoning, watermark-removal attacks, and side
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cr
- Record identifier
- e8ecfca842713d8e9f1fa647d149ff779b35b422e951a5de763678bdb2f79058
- Enrichment time
- 2026-08-12T07:23:25Z
- AI-assisted enrichment
- Yes
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