Comparison Overview
Targa Resources
Targa Resources
811 Louisiana St , Suite 2100, Houston, Texas, US, 77002
Last Update: 27/03/2026
Targa is a leading provider of midstream services as one of the largest independent midstream infrastructure companies in North America. Our operations are critical to the efficient, safe, and reliable delivery of energy across the United States and increasingly to the ...
Chevron
1400 Smith St, Houston, Texas, US, 77002
Last Update: 05/09/2026
Our greatest resource is our people. Their ingenuity, creativity and collaboration have met the complex challenges of energy’s past. Together, we’ll take on the future. We support the LinkedIn Terms of Use (User Agreement), and we expect visitors to our page to do the ...
Compliance Ranges Comparison
Targa Resources
Chevron
Benchmark & Cyber Underwriting Signals
Incidents vs Oil and Gas Industry Avg (This Year)
No incidents recorded for Targa Resources in 2026.
Incidents vs Oil and Gas Industry Avg (This Year)
Chevron has 2.91% fewer incidents than the average of all companies with at least one recorded incident.
Incident History - Targa Resources (X = Date, Y = Severity)
Targa Resources cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Chevron (X = Date, Y = Severity)
Chevron cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Targa Resources
Chevron
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.