cve

7 posts

github

Inside the Advisory Database and what happens when vulnerability volume breaks records (opens in new tab)

Madison Ficorilli is a vulnerability transparency advocate and senior security manager at GitHub. She leads the advisory database curation team and contributes to vulnerability reporting, response, and disclosure through several industry organizations. Her perspective combines current leadership experience with prior roles in incident response and vulnerability coordination. ## Leadership at GitHub - Leads GitHub’s advisory database curation team. - Focuses on improving vulnerability transparency and the quality of security advisory information. ## Industry and Open Source Security Work - Co-chairs a relevant Open Source Security Foundation (OpenSSF) working group. - Serves on the CVE Program Board. - Advocates for effective vulnerability reporting, response, and disclosure practices. ## Professional Background - Previously worked as a product incident response analyst at GitHub. - Served as a vulnerability coordinator at the CERT Coordination Center at Carnegie Mellon University’s Software Engineering Institute. Her career reflects deep expertise across vulnerability coordination, incident response, database curation, and security disclosure policy.

gitlab

5 ways to fix misleading vulnerability severities with policy (opens in new tab)

CVSS scores describe a vulnerability’s general characteristics, not its actual risk in a specific environment. GitLab severity override policies let teams automatically adjust findings based on CVE, CWE, file path, or directory, reducing manual triage. The result is a vulnerability report that better reflects deployment context, exploitability, and organizational priorities. ## How Severity Override Policies Work - Policies run automatically on every default-branch pipeline. - Rules match findings by: - CVE identifier - CWE identifier - File path - Directory - Available actions: - **Set Severity** to informational, low, medium, high, or critical - **Increase Severity** by one level - **Decrease Severity** by one level - Manual overrides by authorized users take precedence. - GitLab records automated changes in vulnerability history and audit events. ## Downgrading Low-Risk CVEs in Internal Services - Internal tools and services may have substantially lower exposure than public-facing applications. - A policy can reduce the severity of selected CVEs found under paths such as `internal/**/*`. - The `decrease` operation lowers severity by one level—for example, Critical to High or High to Medium. - Teams should replace the example CVEs with vulnerabilities they have assessed as less risky in internal deployments. ## Upgrading Injection Vulnerabilities in Production Code - XSS (`CWE-79`) and SQL injection (`CWE-89`) are frequently exploited vulnerability classes. - Findings involving these CWEs under `src/**/*` can be forced to **Critical**. - Combining this override with a merge request approval policy can require security-team review before affected code reaches production. ## Normalizing Severity Across Scanners - SAST, dependency, and container scanners may assign different severities to the same CVE. - A policy can set specific vulnerabilities—such as Log4Shell-related CVEs—to a consistent baseline, such as High. - This produces more predictable triage and approval thresholds across scanning tools. ## Incorporating Exploitation Intelligence - CVSS is largely static and does not reflect changes in real-world exploitation. - EPSS and CISA’s Known Exploited Vulnerabilities catalog provide signals about exploitation likelihood and active attacks. - Teams can explicitly upgrade CVEs identified as actively exploited or highly likely to be exploited, treating them as Critical regardless of their original scanner rating. GitLab severity overrides are most useful when they encode a documented risk model: deployment exposure, vulnerability type, scanner consistency, and current threat intelligence. They should complement—not replace—manual review, auditability, and merge request approval controls.

gitlab

GitLab Patch Release: 18.11.1, 18.10.4, 18.9.6 | GitLab Docs (opens in new tab)

GitLab released patch versions 18.11.1, 18.10.4, and 18.9.6 on April 22, 2026, addressing multiple security vulnerabilities and bugs in CE and EE. Self-managed installations should upgrade immediately, while GitLab.com is already patched and GitLab Dedicated customers need no action. The fixes include unauthenticated GraphQL and browser-based attacks, several denial-of-service flaws, and access-control weaknesses. ## Release Scope and Upgrade Guidance - Applies to GitLab Community Edition and Enterprise Edition. - Affects all deployment types unless otherwise specified, including Omnibus, source installations, and Helm charts. - Recommended fixed versions: - 18.11.1 - 18.10.4 - 18.9.6 - GitLab issues detailing security vulnerabilities are made public 30 days after the relevant patch release. - GitLab publishes both scheduled patch releases, issued on the second and fourth Wednesdays, and ad-hoc critical patches for high-severity vulnerabilities. ## High-Severity Vulnerabilities - **CVE-2026-4922 — GraphQL CSRF** - CVSS 8.1. - An unauthenticated attacker could execute GraphQL mutations on behalf of an authenticated user because of insufficient CSRF protection. - Affects versions before 18.9.6, 18.10.4, and 18.11.1. - **CVE-2026-5816 — Web IDE path validation** - CVSS 8.0. - Under certain conditions, improper path validation could allow unauthenticated attackers to execute arbitrary JavaScript in a user’s browser session. - Affects the 18.10 and 18.11 release lines before the listed patches. - **CVE-2026-5262 — Storybook cross-site scripting** - CVSS 8.0. - Improper input validation could allow unauthenticated access to tokens in the Storybook development environment. - Affects versions from 16.1 through the unpatched 18.9, 18.10, and 18.11 releases. ## Denial-of-Service Fixes - **CVE-2025-0186:** Crafted requests to the discussions endpoint could exhaust server resources. - **CVE-2026-1660:** Improper input validation during Jira issue imports could enable resource exhaustion. - **CVE-2025-6016:** Insufficient limits when retrieving notes could cause service disruption. - **CVE-2025-3922:** Resource-allocation weaknesses in the GraphQL API could allow authenticated users to overwhelm the system. - Each issue carries a CVSS score of 6.5 and generally requires authentication. ## Access-Control and Session Fixes - **CVE-2026-6515 — Virtual registry credentials** - CVSS 5.4. - Invalidated or incorrectly scoped credentials could continue accessing Virtual Registries. - **CVE-2026-5377 — Confidential issue titles** - CVSS 4.3. - Authenticated users could potentially view titles of confidential or private issues in public projects. - **CVE-2026-3254 — Mermaid sandbox** - CVSS 3.5. - Improper validation could allow authenticated users to load unauthorized content into another user’s browser. - The release also lists **CVE-2025-9957**, involving improper access control in the project fork relationship API; the provided text does not include its full impact or severity details. Self-managed GitLab administrators should apply the appropriate patch release as soon as possible, especially because several vulnerabilities permit unauthenticated browser or API attacks.

gitlab

GitLab Patch Release: 18.10.3, 18.9.5, 18.8.9 | GitLab Docs (opens in new tab)

GitLab released patch versions 18.10.3, 18.9.5, and 18.8.9 on April 8, 2026, addressing important security and bug fixes. Self-managed CE and EE installations should upgrade immediately, while GitLab.com is already patched and GitLab Dedicated customers need no action. The fixes cover unauthorized access, denial-of-service vulnerabilities, code injection, XSS, and information disclosure. ## Release Scope and Upgrade Guidance - The patches apply to GitLab Community Edition and Enterprise Edition. - Administrators should upgrade installations affected by the listed vulnerabilities to the latest supported patch release. - GitLab issues describing security vulnerabilities will become public 30 days after the release in which they were fixed. - Patch releases are generally issued on the second and fourth Wednesdays, with urgent ad-hoc releases for critical vulnerabilities. ## Authentication and Authorization Fixes - **CVE-2026-5173 (CVSS 8.5):** Authenticated users could invoke unintended server-side methods through WebSocket connections. - **CVE-2026-2619 (CVSS 4.3):** Auditor users could modify vulnerability flag data in private projects through the AI detection API. - **CVE-2026-1752 (CVSS 4.3):** Developers could modify protected environment settings through authorization flaws in the Environments API. - **CVE-2026-2104:** CSV exports could expose confidential issues assigned to other users because of insufficient authorization checks. ## Denial-of-Service Vulnerabilities - **CVE-2026-1092 (CVSS 7.5):** Unauthenticated attackers could crash or disrupt services through malformed JSON sent to the Terraform state lock API. - **CVE-2025-12664 (CVSS 7.5):** Repeated unauthenticated GraphQL queries could cause denial of service. - **CVE-2026-1403 (CVSS 6.5):** Authenticated users could disrupt Sidekiq workers by importing malformed CSV files. - **CVE-2026-1101 (CVSS 6.5):** Authenticated users could overload GitLab through improperly validated GraphQL SBOM queries. ## Code Execution and Cross-Site Scripting - **CVE-2026-1516 (CVSS 5.7):** Crafted Code Quality report content could leak the IP addresses of users viewing the report. - **CVE-2026-4332 (CVSS 5.4):** Authenticated users could execute arbitrary JavaScript in other users’ browsers through customizable analytics dashboards. ## Information Disclosure - **CVE-2025-9484 (CVSS 4.3):** Certain GraphQL queries could reveal other users’ email addresses to authenticated users. - The release also fixes CSV export authorization issues that could expose confidential issue data. Administrators of self-managed GitLab CE or EE instances should apply 18.10.3, 18.9.5, or 18.8.9 as soon as possible, depending on their supported release branch.

github

A year of open source vulnerability trends: CVEs, advisories, and malware (opens in new tab)

The passage identifies a security professional involved in several major vulnerability-management initiatives. They curate the GitHub Advisory Database, participate in GitHub’s Security Lab, issue CVE IDs, and publish CVE records. ### Responsibilities and Affiliations - Works as a security analyst. - Curates entries in the GitHub Advisory Database. - Is a member of the Security Lab. - Helps issue CVE identifiers for vulnerabilities. - Publishes official CVE records. Overall, the individual contributes to documenting, coordinating, and communicating software security vulnerabilities.

gitlab

Manage vulnerability noise at scale with auto-dismiss policies (opens in new tab)

GitLab’s auto-dismiss vulnerability policies reduce scanner noise by automatically dismissing findings that teams have already determined are irrelevant, non-actionable, or mitigated. Policies match vulnerabilities by file path, directory, or identifier such as a CVE or CWE, while preserving dismissed findings and their audit history. This lets security teams focus on genuine risks without repeatedly performing the same manual triage. ## Why Auto-Dismiss Policies Matter - Security scanners often flag: - Test code and fixtures - Vendored or third-party dependencies - Generated files - Known false positives - Vulnerabilities addressed by existing controls - Manual dismissal creates: - Slower triage - Alert fatigue - Developer friction - Repeated work across projects and pipelines - Auto-dismiss policies allow teams to: - Apply triage decisions consistently at scale - Record a specific dismissal reason - Link findings back to the policy that dismissed them - Keep dismissed vulnerabilities visible for future review ## How Policies Work - Policies are defined in a vulnerability management policy YAML file. - Rules can match: - File paths - Directories - Vulnerability identifiers, including CVEs and CWEs - Teams create the policy through **Secure > Policies > New policy > Vulnerability management policy**. - After the merge request is merged, matching findings on default-branch pipelines are automatically marked **Dismissed**. - GitLab processes up to 1,000 vulnerabilities per pipeline run. - Teams can filter reports by **Dismissed** to evaluate policy impact and verify that the correct findings were handled. ## Dismissing Test Code Findings Test directories commonly contain intentionally insecure credentials, fixtures, or development-only dependencies that do not represent production risk. - Policies can target paths such as: - `test/**/*` - `tests/**/*` - `spec/**/*` - `__tests__/*` - The recommended dismissal reason is `used_in_tests`. ## Dismissing Vendored Dependencies Code in `vendor/`, `third_party/`, `vendored/`, or checked-in `node_modules` is often maintained upstream rather than by the application team. - Directory-based rules can identify these locations. - The example policy uses the `not_applicable` dismissal reason. - Teams should customize the directory patterns to match their repository structure. ## Dismissing Known False-Positive CVEs Repeatedly flagged CVEs that have been confirmed not to apply to an organization’s environment can be dismissed centrally. - Rules match specific identifiers, such as: - `CVE-2023-44487` - `CVE-2024-29041` - `CVE-2023-26136` - The sample policy uses `false_positive`. - The listed CVEs are examples and should be replaced with identifiers validated by the organization. ## Dismissing Generated Code Generated files from Protobuf, gRPC, OpenAPI, ORM, and similar tools may contain patterns scanners flag even though developers do not author or directly patch them. - Example matches include: - `generated/*` - `**/*.pb.go` - `**/*.generated.*` - The suggested dismissal reason is `not_applicable`. ## Dismissing Infrastructure-Mitigated Vulnerabilities Some vulnerabilities may be addressed by enforced runtime controls, such as WAF rules. - The example targets: - `CWE-79` for cross-site scripting - `CWE-89` for SQL injection - It uses the `mitigating_control` dismissal reason. - This approach should only be used when the mitigation is verified, consistently deployed, and reliably protects all affected paths. ## Practical Recommendation Use auto-dismiss policies for well-understood, documented cases—not as a substitute for vulnerability investigation. Start with narrowly scoped path or identifier rules, review the dismissed results regularly, and ensure every dismissal reason reflects a decision that remains valid.

kakao

YEYE is Watching – (opens in new tab)

Kakao developed YEYE, a dedicated Attack Surface Management (ASM) system, to proactively identify and manage the organization's vast digital footprint, including IPs, domains, and open ports. By integrating automated scanning with a human-led Daily Security Review (DSR) process, the platform transforms raw asset data into actionable security intelligence. This holistic approach ensures that potential entry points are identified and secured before they can be exploited by external threats. ## The YEYE Asset Management Framework * Defines attack surfaces broadly to include every external-facing digital asset, such as subdomains, API endpoints, and mobile APKs. * Categorizes assets using a standardized taxonomy based on scope (In/Out/Undefined), type (Domain/IP/Service), and identification status (Known/Unknown/3rd Party). * Implements a labeling system that converts diverse data formats from multiple sources into a simplified, unified structure for better visibility. * Establishes multi-dimensional relationships between assets, CVEs, certificates, and departments, allowing teams to instantly identify which business unit is responsible for a newly discovered vulnerability. ## Daily Security Review (DSR) * Operates on the principle that "security is a process, not a product," bridging the gap between automated detection and manual remediation. * Utilizes a rotating group system where security engineers review external feeds, public vulnerability news, and YEYE alerts every morning. * Focuses on detecting "shadow IT" or assets deployed without formal security reviews to ensure all external touchpoints are accounted for. ## Scalable and Efficient Scanning Architecture * Resolved internal network bandwidth bottlenecks by adopting a hybrid infrastructure that leverages public cloud resources for high-concurrency scanning tasks. * Developed a custom distributed scanning structure using schedulers and queues to manage multiple independent workers, overcoming the limitations of single-process open-source scanners. * Optimized infrastructure costs by identifying the "sweet spot" in server specifications, favoring the horizontal expansion of medium-spec servers over expensive, high-performance hardware. * Mitigates service impact and false alarms by using fixed IPs and custom User-Agent (UA) strings, allowing service owners to distinguish YEYE’s security probes from actual malicious traffic. To effectively manage a growing attack surface, organizations should combine automated asset discovery with a structured manual review process. Prioritizing data standardization and relationship mapping between assets and vulnerabilities is essential for rapid incident response and long-term infrastructure hardening.