Comparison Overview
JCPenney
JCPenney
6502 Legacy Drive, Plano, 75024, US
Last Update: 17/06/2026
As we reinvent ourselves to fit the diversity of America, we are looking for motivated, talented people who can emerge as Warriors in our organization. JCPenney offers an inclusive environment and culture where you can find and define yourself - your style, your purpos...
TFG (The Foschini Group)
340 Voortrekker Road, Cape Town, 7500, ZA
Last Update: 13/09/2026
TFG holds a diversified portfolio of speciality retail assets across various product categories and consumer segments. The Group has a portfolio of 35 leading retail brands, with over 4600 outlets in 23 countries on five continents, offering customers a variety of speci...
Compliance Ranges Comparison
JCPenney
TFG (The Foschini Group)
Benchmark & Cyber Underwriting Signals
Incidents vs Retail Industry Avg (This Year)
JCPenney has 44.75% fewer incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Retail Industry Avg (This Year)
No incidents recorded for TFG (The Foschini Group) in 2026.
Incident History - JCPenney (X = Date, Y = Severity)
JCPenney cyber incidents detection timeline including parent company and subsidiaries.
Incident History - TFG (The Foschini Group) (X = Date, Y = Severity)
TFG (The Foschini Group) cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
JCPenney
TFG (The Foschini 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.