Comparison Overview
LogMeIn
LogMeIn
333 Summer St, Boston, 02210, US
Last Update: 17/07/2026
LogMeIn, Inc.’s category-defining products unlock the potential of the modern workforce by making it possible for millions of people and businesses around the globe to do their best work, whenever, however, and most importantly, wherever. A pioneer in remote work techno...
Booking.com
Oosterdokskade 163, Amsterdam, 1011 DL, NL
Last Update: 13/09/2026
A career at Booking.com is all about the journey, helping you explore new challenges in a place where you can be your best self. With plenty of exciting twists, turns and opportunities along the way. We’ve always been pioneers, on a mission to shape the future of trav...
Compliance Ranges Comparison
LogMeIn
Booking.com
Benchmark & Cyber Underwriting Signals
Incidents vs Software Development Industry Avg (This Year)
LogMeIn has 6.54% fewer incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Software Development Industry Avg (This Year)
Booking.com has 288.35% more incidents than the average of all companies with at least one recorded incident.
Incident History - LogMeIn (X = Date, Y = Severity)
LogMeIn cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Booking.com (X = Date, Y = Severity)
Booking.com cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
LogMeIn
Booking.com
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.