Comparison Overview
Gartner
Gartner
56 Top Gallant Street, Stamford, 06904, US
Last Update: 05/09/2026
We deliver actionable, objective business and technology insights. Our expert guidance and tools enable faster, smarter decisions and stronger performance on an organization’s mission-critical priorities. Our unrivaled combination of business and technology insights st...
GLG
60 East 42nd Street, 3rd Floor, New York, NY, US, 10165
Last Update: 05/09/2026
GLG is the world’s largest insight network. We connect decision makers to the right experts so they can act with the confidence that comes from true clarity and have what it takes to get ahead. Our network of experts is the world’s largest source of first-hand expertise...
Compliance Ranges Comparison
Gartner
GLG
Benchmark & Cyber Underwriting Signals
Incidents vs Information Services Industry Avg (This Year)
Gartner has 54.75% fewer incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Information Services Industry Avg (This Year)
No incidents recorded for GLG in 2026.
Incident History - Gartner (X = Date, Y = Severity)
Gartner cyber incidents detection timeline including parent company and subsidiaries.
Incident History - GLG (X = Date, Y = Severity)
GLG cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Gartner
GLG
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.