Comparison Overview
Arkema Battery Solutions
Arkema Battery Solutions
51, Esplanade du Général de Gaulle, La Défense, Puteaux, Île-de-France, FR, 92800
Last Update: 01/04/2026
Arkema offers the market-leading portfolio of specialty materials for inside and outside the battery cell. We design advanced solutions that help to optimize performance and improve the battery energy density, duration, weight reduction and recharging time. Along with t...
IFF
521 West 57th Street , New York, New York, US, 10019
Last Update: 14/09/2026
At IFF, we make joy through science, creativity and heart. As the global leader in flavors, fragrances, food ingredients, health and biosciences, we deliver groundbreaking, sustainable innovations that elevate everyday products—advancing wellness, delighting the senses ...
Compliance Ranges Comparison
Arkema Battery Solutions
IFF
Benchmark & Cyber Underwriting Signals
Incidents vs Chemical Manufacturing Industry Avg (This Year)
No incidents recorded for Arkema Battery Solutions in 2026.
Incidents vs Chemical Manufacturing Industry Avg (This Year)
No incidents recorded for IFF in 2026.
Incident History - Arkema Battery Solutions (X = Date, Y = Severity)
Arkema Battery Solutions cyber incidents detection timeline including parent company and subsidiaries.
Incident History - IFF (X = Date, Y = Severity)
IFF cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Arkema Battery Solutions
IFF
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.