Comparison Overview
Bajaj Auto Ltd
Bajaj Auto Ltd
Bajaj Auto Ltd, Mumbai - Pune Road, Akurdi, Pune, Maharashtra, IN, 411035
Last Update: 14/09/2026
A journey that began 75 years ago in a corner of India and has since traversed the world over. Uniting people from across countries, cultures, and customs over the years with a multitude of different dreams, there's power in an idea. An idea that gave rise to brands tha...
RPG Group
RPG House, Mumbai, 400030, IN
Last Update: 05/09/2026
RPG Group, headquartered in Mumbai, is a fast-growing diversified business group with a turnover in excess of US$5.2 billion. The Group has a presence in the core sectors of the economy - Infrastructure (KEC International), Mobility (CEAT), Information Technology (Zensa...
Compliance Ranges Comparison
Bajaj Auto Ltd
RPG Group
Benchmark & Cyber Underwriting Signals
Incidents vs Manufacturing Industry Avg (This Year)
Bajaj Auto Ltd has 60.0% fewer incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Manufacturing Industry Avg (This Year)
No incidents recorded for RPG Group in 2026.
Incident History - Bajaj Auto Ltd (X = Date, Y = Severity)
Bajaj Auto Ltd cyber incidents detection timeline including parent company and subsidiaries.
Incident History - RPG Group (X = Date, Y = Severity)
RPG Group cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Bajaj Auto Ltd
RPG Group
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.