In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the Shard API in TensorFlow expects the last argument to be a function taking two int64 (i.e., long long) arguments. However, there are several places in TensorFlow where a lambda taking int or int32 arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
| Software | From | Fixed in |
|---|---|---|
| google / tensorflow | - | 1.15.4 |
| google / tensorflow | 2.0.0 | 2.0.3 |
| google / tensorflow | 2.1.0 | 2.1.2 |
| google / tensorflow | 2.2.0 | 2.2.1 |
| google / tensorflow | 2.3.0 | 2.3.1 |
| opensuse / leap | 15.2 | 15.2.x |
tensorflow
|
- | 1.15.4 |
tensorflow
|
2.0.0 | 2.0.3 |
tensorflow
|
2.1.0 | 2.1.2 |
tensorflow
|
2.2.0 | 2.2.0.x |
tensorflow
|
2.2.0 | 2.2.1 |
tensorflow
|
2.3.0 | 2.3.0.x |
tensorflow
|
2.3.0 | 2.3.1 |
tensorflow-cpu
|
- | 1.15.4 |
tensorflow-cpu
|
2.0.0 | 2.0.3 |
tensorflow-cpu
|
2.1.0 | 2.1.2 |
tensorflow-cpu
|
2.2.0 | 2.2.0.x |
tensorflow-cpu
|
2.2.0 | 2.2.1 |
tensorflow-cpu
|
2.3.0 | 2.3.0.x |
tensorflow-cpu
|
2.3.0 | 2.3.1 |
tensorflow-gpu
|
- | 1.15.4 |
tensorflow-gpu
|
2.0.0 | 2.0.3 |
tensorflow-gpu
|
2.1.0 | 2.1.2 |
tensorflow-gpu
|
2.2.0 | 2.2.0.x |
tensorflow-gpu
|
2.2.0 | 2.2.1 |
tensorflow-gpu
|
2.3.0 | 2.3.0.x |
tensorflow-gpu
|
2.3.0 | 2.3.1 |
A security vulnerability is a weakness in software, hardware, or configuration that can be exploited to compromise confidentiality, integrity, or availability. Many vulnerabilities are tracked as CVEs (Common Vulnerabilities and Exposures), which provide a standardized identifier so teams can coordinate patching, mitigation, and risk assessment across tools and vendors.
CVSS (Common Vulnerability Scoring System) estimates technical severity, but it doesn't automatically equal business risk. Prioritize using context like internet exposure, affected asset criticality, known exploitation (proof-of-concept or in-the-wild), and whether compensating controls exist. A "Medium" CVSS on an exposed, production system can be more urgent than a "Critical" on an isolated, non-production host.
A vulnerability is the underlying weakness. An exploit is the method or code used to take advantage of it. A zero-day is a vulnerability that is unknown to the vendor or has no publicly available fix when attackers begin using it. In practice, risk increases sharply when exploitation becomes reliable or widespread.
Recurring findings usually come from incomplete Asset Discovery, inconsistent patch management, inherited images, and configuration drift. In modern environments, you also need to watch the software supply chain: dependencies, containers, build pipelines, and third-party services can reintroduce the same weakness even after you patch a single host. Unknown or unmanaged assets (often called Shadow IT) are a common reason the same issues resurface.
Use a simple, repeatable triage model: focus first on externally exposed assets, high-value systems (identity, VPN, email, production), vulnerabilities with known exploits, and issues that enable remote code execution or privilege escalation. Then enforce patch SLAs and track progress using consistent metrics so remediation is steady, not reactive.
SynScan combines attack surface monitoring and continuous security auditing to keep your inventory current, flag high-impact vulnerabilities early, and help you turn raw findings into a practical remediation plan.