Comparison Overview
LGC LoGiCal
LGC LoGiCal
Queens Road, Teddington, TW11 0LY, GB
Last Update: 11/12/2025
LGC Standards LoGiCal provides laboratories with a conveniently packaged wide range of reference materials, focused on forensic and clinical toxicology. Since being launched 2012, the portfolio has continually grown and now covers drugs, metabolites and stable isotope...
Airgas
259 N. Radnor-Chester Road, Radnor, 19087, US
Last Update: 14/09/2026
Airgas, an Air Liquide company, is a leading U.S. supplier of industrial, medical and specialty gases, as well as hardgoods and related products; one of the largest U.S. suppliers of safety products; and a leading U.S. supplier of ammonia products and process chemicals....
Compliance Ranges Comparison
LGC LoGiCal
Airgas
Benchmark & Cyber Underwriting Signals
Incidents vs Chemical Manufacturing Industry Avg (This Year)
No incidents recorded for LGC LoGiCal in 2026.
Incidents vs Chemical Manufacturing Industry Avg (This Year)
No incidents recorded for Airgas in 2026.
Incident History - LGC LoGiCal (X = Date, Y = Severity)
LGC LoGiCal cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Airgas (X = Date, Y = Severity)
Airgas cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
LGC LoGiCal
Airgas
FAQ
Latest Global CVEs
vLLM through 0.29.0 fails to properly clean up decode-side metadata for rejected inference requests in prefill/decode disaggregated deployments. Remote attackers can submit requests with max_tokens=0 to exhaust decode-worker memory without bound until the worker restarts.
- https://github.com/vllm-project/vllm
- https://github.com/vllm-project/vllm/blob/v0.29.0/vllm/distributed/kv_transfer/kv_connector/v1/nixl/push_worker.py#L162-L181
- https://github.com/vllm-project/vllm/pull/55677
- https://www.vulncheck.com/advisories/vllm-through-0.29.0-memory-exhaustion-via-rejected-requests
redis-parser through 3.0.0 contains a denial of service vulnerability in the RESP protocol parser that allows malicious Redis endpoints to crash the client process through unbounded recursion on nested arrays. Attackers can send crafted RESP byte streams with repeated array headers that exhaust the V8 call stack, causing an uncaught RangeError that terminates the Node.js process without triggering error handling callbacks.
- https://github.com/NodeRedis/node-redis-parser
- https://github.com/NodeRedis/node-redis-parser/blob/701655430f5f7d9ca00892a02f7eefcbc1193a98/lib/parser.js#L204-L213
- https://github.com/NodeRedis/node-redis-parser/blob/701655430f5f7d9ca00892a02f7eefcbc1193a98/lib/parser.js#L291-L306
- https://github.com/redis/ioredis/issues/2108
- https://www.vulncheck.com/advisories/redis-parser-through-3.0.0-denial-of-service-via-unbounded-recursion
Improper neutralization of special elements in output used by a downstream component ('injection') in Azure Cosmos DB allows an authorized attacker to elevate privileges over a network.
Server-side request forgery (ssrf) in Azure AI Foundry allows an unauthorized attacker to elevate privileges over a network.
Missing authentication for critical function in Azure AI Foundry allows an unauthorized attacker to elevate privileges over a network.