LangChain
Company Details
Linkedin ID:
langchain
Website:
Employees number:
187
Number of followers:
477,971
NAICS:
513
Industry Type:
Homepage:
langchain.com
IP Addresses:
0
Company ID:
LAN_6814675
Scan Status:
In-progress
LangChain Company CyberSecurity Posture
langchain.com
LangChain provides the agent engineering platform and open source frameworks developers need to ship reliable agents fast.
LangChain A.I CyberSecurity Scoring
LangChain Risk Score (AI oriented)Between 750 and 799
LangChain
Updated:
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LangChain Global Score (TPRM)XXXX
LangChain
- Instant access to detailed risk factors
- Benchmark vs. industry & size peers
- Vulnerabilities
- Findings
LangChain Company CyberSecurity News & History
Past Incidents
2
Attack Types
1
LangChain
Vulnerability
Rankiteo Explanation
Attack threatening the organization's existence
Description: Cybersecurity researchers at Noma Security disclosed a critical vulnerability dubbed AgentSmith in LangChain‘s LangSmith platform, specifically affecting its public Prompt Hub. This flaw, with a CVSS score of 8.8, could allow malicious AI agents to steal sensitive user data, including OpenAI API keys, and manipulate responses from large language models (LLMs). The vulnerability exploited harmful proxy configurations, enabling attackers to gain unauthorized access to victims' OpenAI accounts, potentially downloading sensitive datasets, inferring confidential information, or causing financial losses by exhausting API usage quotas. In advanced attacks, the malicious proxy could alter LLM responses, leading to fraud or incorrect automated decisions. LangChain confirmed the issue and deployed a fix, introducing new safety measures to prevent future exploitation.
LangChain: A message from John Furrier, co-founder of SiliconANGLE:
Vulnerability
Rankiteo Explanation
Attack threatening the organization's existence
Description: **Critical ‘LangGrinch’ Vulnerability in LangChain-Core Exposes AI Agent Secrets** A recently disclosed high-severity vulnerability, dubbed **LangGrinch**, affects *langchain-core*—a foundational library powering AI agents in production environments. The flaw, tracked with a **CVSS score of 9.3**, stems from an insecure serialization and deserialization process in the library’s helper functions. Attackers can exploit it via **prompt injection**, tricking AI agents into generating structured outputs containing LangChain’s internal marker key. When improperly escaped during serialization, this data can later be deserialized as a trusted object, enabling malicious actions. The vulnerability resides in *langchain-core* itself, a core dependency for frameworks and applications across the AI ecosystem. With **847 million total downloads** and **tens of millions monthly**, the library is deeply embedded in modern AI workflows. Exploitation could lead to **full environment variable exfiltration**, including cloud credentials, database connection strings, vector database secrets, and LLM API keys—potentially escalating to **remote code execution** under certain conditions. Security researchers at **Cyata** identified **12 distinct exploit flows**, demonstrating how routine agent operations—such as persisting, streaming, or reconstructing structured data—can inadvertently open attack paths. Notably, the flaw lies in the **serialization path**, not deserialization, expanding the attack surface reachable from a single prompt. Cyata emphasized the risk of the vulnerability residing in the ecosystem’s **"plumbing layer,"** making it particularly dangerous for production systems. Patches are available in *langchain-core* **versions 1.2.5 and 0.3.81**, following **ethical disclosure** to LangChain’s maintainers, who implemented remediation and additional security hardening. The discovery underscores the evolving security challenges of **agentic AI**, where governance and permission boundaries become critical as systems move into production.
LangChain Company Scoring based on AI Models
Cyber Incidents Likelihood 3 - 6 - 9 months
A.I Risk Score Likelihood 3 - 6 - 9 months
Underwriter Stats for LangChain
Incidents vs Technology, Information and Internet Industry Average (This Year)
LangChain has 104.08% more incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs All-Companies Average (This Year)
LangChain has 153.16% more incidents than the average of all companies with at least one recorded incident.
Incident Types LangChain vs Technology, Information and Internet Industry Avg (This Year)
LangChain reported 2 incidents this year: 0 cyber attacks, 0 ransomware, 2 vulnerabilities, 0 data breaches, compared to industry peers with at least 1 incident.
Incident History — LangChain (X = Date, Y = Severity)
LangChain cyber incidents detection timeline including parent company and subsidiaries
LangChain Company Subsidiaries
LangChain provides the agent engineering platform and open source frameworks developers need to ship reliable agents fast.
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LangChain CyberSecurity News
December 27, 2025 12:42 PM
LangGrinch Vulnerability Exposes LangChain AI to Secret Theft Risks
In the fast-evolving world of artificial intelligence development, a newly disclosed vulnerability has sent shockwaves through the community...
December 27, 2025 02:33 AM
M-Files Vulnerability Let Attacker Capture Session Tokens of Other Active Users
An M-Files Server flaw lets authenticated attackers capture session tokens and access documents without authorization.
December 26, 2025 12:31 PM
LangGrinch Vulnerability in LangChain Core Enables RCE via Prompt Injections
In the fast-evolving world of artificial intelligence development, frameworks like LangChain have become indispensable tools for building...
December 26, 2025 09:27 AM
Critical LangChain Core Vulnerability Exposes Secrets via Serialization Injection
A critical LangChain Core vulnerability (CVE-2025-68664, CVSS 9.3) allows secret theft and prompt injection through unsafe serialization;...
December 26, 2025 06:00 AM
Critical LangChain Vulnerability Allows Attackers to Steal Sensitive Secrets
A critical security vulnerability in LangChain, enables attackers to extract environment variable secrets and, through a serialization...
December 26, 2025 02:48 AM
Critical Langchain Vulnerability Let attackers Exfiltrate Sensitive Secrets from AI systems
A critical vulnerability in LangChain's core library (CVE-2025-68664) allows attackers to exfiltrate sensitive environment variables and...
December 11, 2025 08:00 AM
GitLab Patches Multiple Vulnerabilities that Allows Attackers to Trigger XSS and DoS Attack
Critical security patches on December 10, 2025, addressing ten significant vulnerabilities across its Community Edition and Enterprise...
December 05, 2025 08:00 AM
Cacti Command Injection Vulnerability Let Attackers Execute Malicious Code Remotely
Command injection flaw in the open-source network monitoring tool Cacti allows authenticated attackers to execute arbitrary code.
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Frequently Asked Questions
Explore insights on cybersecurity incidents, risk posture, and Rankiteo's assessments.
LangChain CyberSecurity History Information
Official Website of LangChain
The official website of LangChain is http://langchain.com.
LangChain’s AI-Generated Cybersecurity Score
According to Rankiteo, LangChain’s AI-generated cybersecurity score is 754, reflecting their Fair security posture.
How many security badges does LangChain’ have ?
According to Rankiteo, LangChain currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.
Does LangChain have SOC 2 Type 1 certification ?
According to Rankiteo, LangChain is not certified under SOC 2 Type 1.
Does LangChain have SOC 2 Type 2 certification ?
According to Rankiteo, LangChain does not hold a SOC 2 Type 2 certification.
Does LangChain comply with GDPR ?
According to Rankiteo, LangChain is not listed as GDPR compliant.
Does LangChain have PCI DSS certification ?
According to Rankiteo, LangChain does not currently maintain PCI DSS compliance.
Does LangChain comply with HIPAA ?
According to Rankiteo, LangChain is not compliant with HIPAA regulations.
Does LangChain have ISO 27001 certification ?
According to Rankiteo,LangChain is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.
Industry Classification of LangChain
LangChain operates primarily in the Technology, Information and Internet industry.
Number of Employees at LangChain
LangChain employs approximately 187 people worldwide.
Subsidiaries Owned by LangChain
LangChain presently has no subsidiaries across any sectors.
LangChain’s LinkedIn Followers
LangChain’s official LinkedIn profile has approximately 477,971 followers.
NAICS Classification of LangChain
LangChain is classified under the NAICS code 513, which corresponds to Others.
LangChain’s Presence on Crunchbase
Yes, LangChain has an official profile on Crunchbase, which can be accessed here: https://www.crunchbase.com/organization/langchain.
LangChain’s Presence on LinkedIn
Yes, LangChain maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/langchain.
Cybersecurity Incidents Involving LangChain
As of December 29, 2025, Rankiteo reports that LangChain has experienced 2 cybersecurity incidents.
Number of Peer and Competitor Companies
LangChain has an estimated 13,302 peer or competitor companies worldwide.
What types of cybersecurity incidents have occurred at LangChain ?
Incident Types: The types of cybersecurity incidents that have occurred include Vulnerability.
How does LangChain detect and respond to cybersecurity incidents ?
Detection and Response: The company detects and responds to cybersecurity incidents through an third party assistance with noma security, and containment measures with swift deployment of a fix, and remediation measures with new safety measures, remediation measures with warning messages, remediation measures with persistent banner on agent description pages, and third party assistance with cyata (security researchers), and containment measures with patches released in langchain-core versions 1.2.5 and 0.3.81, and remediation measures with security hardening steps beyond the immediate fix, and communication strategy with ethical disclosure to langchain maintainers, public advisory by cyata..
Incident Details
Can you provide details on each incident ?
Title: AgentSmith Vulnerability in LangChain's LangSmith Platform
Description: Cybersecurity researchers at Noma Security disclosed a critical vulnerability within LangChain‘s LangSmith platform, affecting its public Prompt Hub. This flaw, dubbed AgentSmith with a CVSS score of 8.8, allows malicious AI agents to steal sensitive user data and manipulate responses from large language models (LLMs).
Date Detected: 2024-10-29
Date Publicly Disclosed: 2024-11-06
Date Resolved: 2024-11-06
Type: Vulnerability Exploit
Attack Vector: Man-in-the-Middle (MITM)
Vulnerability Exploited: Hidden malicious proxy in AI agents
Motivation: Data theftUnauthorized accessFinancial lossFraud
Title: LangGrinch Vulnerability in langchain-core
Description: A critical vulnerability in langchain-core, dubbed 'LangGrinch,' allows attackers to exploit a serialization and deserialization injection vulnerability. This flaw enables the exfiltration of sensitive secrets, including environment variables, cloud provider credentials, and API keys, and could potentially escalate to remote code execution under certain conditions.
Type: Serialization/Deserialization Injection
Attack Vector: Prompt Injection
Vulnerability Exploited: Improper escaping of LangChain’s internal marker key during serialization
What are the most common types of attacks the company has faced ?
Common Attack Types: The most common types of attacks the company has faced is Vulnerability.
How does the company identify the attack vectors used in incidents ?
Identification of Attack Vectors: The company identifies the attack vectors used in incidents through Public Prompt Hub.
Impact of the Incidents
What was the impact of each incident ?
Incident : Vulnerability Exploit LAN901061825
Data Compromised: Openai api keys, Uploaded files, Voice inputs
Systems Affected: LangSmith's Prompt Hub
Incident : Serialization/Deserialization Injection LAN1766986573
Data Compromised: Environment variables, cloud provider credentials, database and RAG connection strings, vector database secrets, LLM API keys
Systems Affected: AI agent frameworks and applications using langchain-core
Operational Impact: Potential full environment variable exfiltration, remote code execution under certain conditions
What types of data are most commonly compromised in incidents ?
Commonly Compromised Data Types: The types of data most commonly compromised in incidents are Openai Api Keys, Uploaded Files, Voice Inputs, , Environment variables, credentials and API keys.
Which entities were affected by each incident ?
Incident : Vulnerability Exploit LAN901061825
Entity Name: LangChain
Entity Type: Company
Industry: AI and Technology
Incident : Serialization/Deserialization Injection LAN1766986573
Entity Name: LangChain-based AI applications and frameworks
Entity Type: AI Framework/Library
Industry: Artificial Intelligence, Technology
Location: Global
Size: Tens of millions of downloads (847M total downloads of langchain-core)
Response to the Incidents
What measures were taken in response to each incident ?
Incident : Vulnerability Exploit LAN901061825
Third Party Assistance: Noma Security
Containment Measures: Swift deployment of a fix
Remediation Measures: New safety measuresWarning messagesPersistent banner on agent description pages
Incident : Serialization/Deserialization Injection LAN1766986573
Third Party Assistance: Cyata (security researchers)
Containment Measures: Patches released in langchain-core versions 1.2.5 and 0.3.81
Remediation Measures: Security hardening steps beyond the immediate fix
Communication Strategy: Ethical disclosure to LangChain Maintainers, public advisory by Cyata
How does the company involve third-party assistance in incident response ?
Third-Party Assistance: The company involves third-party assistance in incident response through Noma Security, Cyata (security researchers).
Data Breach Information
What type of data was compromised in each breach ?
Incident : Vulnerability Exploit LAN901061825
Type of Data Compromised: Openai api keys, Uploaded files, Voice inputs
Sensitivity of Data: High
Incident : Serialization/Deserialization Injection LAN1766986573
Type of Data Compromised: Environment variables, credentials, API keys
Sensitivity of Data: High (cloud provider credentials, database secrets, LLM API keys)
Data Exfiltration: Yes (via outbound HTTP requests)
What measures does the company take to prevent data exfiltration ?
Prevention of Data Exfiltration: The company takes the following measures to prevent data exfiltration: New safety measures, Warning messages, Persistent banner on agent description pages, , Security hardening steps beyond the immediate fix.
How does the company handle incidents involving personally identifiable information (PII) ?
Handling of PII Incidents: The company handles incidents involving personally identifiable information (PII) through by swift deployment of a fix and patches released in langchain-core versions 1.2.5 and 0.3.81.
Lessons Learned and Recommendations
What lessons were learned from each incident ?
Incident : Vulnerability Exploit LAN901061825
Lessons Learned: Need for organizations to enhance AI security practices, maintain a centralized inventory of AI agents, implement runtime protections, and enforce strong security governance.
Incident : Serialization/Deserialization Injection LAN1766986573
Lessons Learned: Agentic AI systems require tight defaults, clear boundaries, and the ability to reduce blast radius. Security must shift from 'what code do we run' to 'what effective permissions does this system end up exercising.'
What recommendations were made to prevent future incidents ?
Incident : Vulnerability Exploit LAN901061825
Recommendations: Maintain a centralized inventory of AI agents using an AI BOM, Implement runtime protections, Enforce strong security governanceMaintain a centralized inventory of AI agents using an AI BOM, Implement runtime protections, Enforce strong security governanceMaintain a centralized inventory of AI agents using an AI BOM, Implement runtime protections, Enforce strong security governance
Incident : Serialization/Deserialization Injection LAN1766986573
Recommendations: Update to langchain-core versions 1.2.5 or 0.3.81 immediately. Implement security hardening steps for agentic AI systems.
What are the key lessons learned from past incidents ?
Key Lessons Learned: The key lessons learned from past incidents are Need for organizations to enhance AI security practices, maintain a centralized inventory of AI agents, implement runtime protections, and enforce strong security governance.Agentic AI systems require tight defaults, clear boundaries, and the ability to reduce blast radius. Security must shift from 'what code do we run' to 'what effective permissions does this system end up exercising.'.
What recommendations has the company implemented to improve cybersecurity ?
Implemented Recommendations: The company has implemented the following recommendations to improve cybersecurity: Update to langchain-core versions 1.2.5 or 0.3.81 immediately. Implement security hardening steps for agentic AI systems..
References
Where can I find more information about each incident ?
Incident : Vulnerability Exploit LAN901061825
Source: Noma Security
Incident : Vulnerability Exploit LAN901061825
Source: Hackread.com
Incident : Serialization/Deserialization Injection LAN1766986573
Source: SiliconANGLE Media
Incident : Serialization/Deserialization Injection LAN1766986573
Source: Cyata
Where can stakeholders find additional resources on cybersecurity best practices ?
Additional Resources: Stakeholders can find additional resources on cybersecurity best practices at and Source: Noma Security, and Source: Hackread.com, and Source: SiliconANGLE Media, and Source: Cyata.
Investigation Status
What is the current status of the investigation for each incident ?
Incident : Vulnerability Exploit LAN901061825
Investigation Status: Resolved
Incident : Serialization/Deserialization Injection LAN1766986573
Investigation Status: Vulnerability patched and publicly disclosed
How does the company communicate the status of incident investigations to stakeholders ?
Communication of Investigation Status: The company communicates the status of incident investigations to stakeholders through Ethical disclosure to LangChain Maintainers and public advisory by Cyata.
Stakeholder and Customer Advisories
Were there any advisories issued to stakeholders or customers for each incident ?
Incident : Serialization/Deserialization Injection LAN1766986573
Stakeholder Advisories: Urgent update recommended for all organizations using langchain-core
What advisories does the company provide to stakeholders and customers following an incident ?
Advisories Provided: The company provides the following advisories to stakeholders and customers following an incident: was Urgent update recommended for all organizations using langchain-core.
Initial Access Broker
How did the initial access broker gain entry for each incident ?
Incident : Vulnerability Exploit LAN901061825
Entry Point: Public Prompt Hub
Post-Incident Analysis
What were the root causes and corrective actions taken for each incident ?
Incident : Vulnerability Exploit LAN901061825
Root Causes: Vulnerability in public Prompt Hub allowing malicious proxy configurations
Corrective Actions: Deploying A Fix, Introducing New Safety Measures, Warning Messages, Persistent Banner On Agent Description Pages,
Incident : Serialization/Deserialization Injection LAN1766986573
Root Causes: Improper escaping of LangChain’s internal marker key during serialization, allowing untrusted user input to be interpreted as trusted LangChain objects during deserialization.
Corrective Actions: Patches released, security hardening steps implemented, and ethical disclosure process followed.
What is the company's process for conducting post-incident analysis ?
Post-Incident Analysis Process: The company's process for conducting post-incident analysis is described as Noma Security, Cyata (security researchers).
What corrective actions has the company taken based on post-incident analysis ?
Corrective Actions Taken: The company has taken the following corrective actions based on post-incident analysis: Deploying A Fix, Introducing New Safety Measures, Warning Messages, Persistent Banner On Agent Description Pages, , Patches released, security hardening steps implemented, and ethical disclosure process followed..
Additional Questions
Incident Details
What was the most recent incident detected ?
Most Recent Incident Detected: The most recent incident detected was on 2024-10-29.
What was the most recent incident publicly disclosed ?
Most Recent Incident Publicly Disclosed: The most recent incident publicly disclosed was on 2024-11-06.
What was the most recent incident resolved ?
Most Recent Incident Resolved: The most recent incident resolved was on 2024-11-06.
Impact of the Incidents
What was the most significant data compromised in an incident ?
Most Significant Data Compromised: The most significant data compromised in an incident were OpenAI API keys, Uploaded files, Voice inputs, , Environment variables, cloud provider credentials, database and RAG connection strings, vector database secrets and LLM API keys.
Response to the Incidents
What third-party assistance was involved in the most recent incident ?
Third-Party Assistance in Most Recent Incident: The third-party assistance involved in the most recent incident was Noma Security, Cyata (security researchers).
What containment measures were taken in the most recent incident ?
Containment Measures in Most Recent Incident: The containment measures taken in the most recent incident were Swift deployment of a fix and Patches released in langchain-core versions 1.2.5 and 0.3.81.
Data Breach Information
What was the most sensitive data compromised in a breach ?
Most Sensitive Data Compromised: The most sensitive data compromised in a breach were OpenAI API keys, Uploaded files, Environment variables, cloud provider credentials, database and RAG connection strings, vector database secrets, LLM API keys and Voice inputs.
Lessons Learned and Recommendations
What was the most significant lesson learned from past incidents ?
Most Significant Lesson Learned: The most significant lesson learned from past incidents was Need for organizations to enhance AI security practices, maintain a centralized inventory of AI agents, implement runtime protections, and enforce strong security governance., Agentic AI systems require tight defaults, clear boundaries, and the ability to reduce blast radius. Security must shift from 'what code do we run' to 'what effective permissions does this system end up exercising.'.
What was the most significant recommendation implemented to improve cybersecurity ?
Most Significant Recommendation Implemented: The most significant recommendation implemented to improve cybersecurity was Update to langchain-core versions 1.2.5 or 0.3.81 immediately. Implement security hardening steps for agentic AI systems., Maintain a centralized inventory of AI agents using an AI BOM, Enforce strong security governance and Implement runtime protections.
References
What is the most recent source of information about an incident ?
Most Recent Source: The most recent source of information about an incident are Hackread.com, Cyata, Noma Security and SiliconANGLE Media.
Investigation Status
What is the current status of the most recent investigation ?
Current Status of Most Recent Investigation: The current status of the most recent investigation is Resolved.
Stakeholder and Customer Advisories
What was the most recent stakeholder advisory issued ?
Most Recent Stakeholder Advisory: The most recent stakeholder advisory issued was Urgent update recommended for all organizations using langchain-core, .
Initial Access Broker
What was the most recent entry point used by an initial access broker ?
Most Recent Entry Point: The most recent entry point used by an initial access broker was an Public Prompt Hub.
Post-Incident Analysis
What was the most significant root cause identified in post-incident analysis ?
Most Significant Root Cause: The most significant root cause identified in post-incident analysis was Vulnerability in public Prompt Hub allowing malicious proxy configurations, Improper escaping of LangChain’s internal marker key during serialization, allowing untrusted user input to be interpreted as trusted LangChain objects during deserialization..
What was the most significant corrective action taken based on post-incident analysis ?
Most Significant Corrective Action: The most significant corrective action taken based on post-incident analysis was Deploying a fixIntroducing new safety measuresWarning messagesPersistent banner on agent description pages, Patches released, security hardening steps implemented, and ethical disclosure process followed..
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Latest Global CVEs (Not Company-Specific)
Description
A vulnerability was found in Tenda WH450 1.0.0.18. Affected is an unknown function of the file /goform/PPTPUserSetting. Performing manipulation of the argument delno results in stack-based buffer overflow. Remote exploitation of the attack is possible. The exploit has been made public and could be used.
Risk Information
cvss2
Base: 8.3
Severity: LOW
AV:N/AC:L/Au:M/C:C/I:C/A:C
cvss3
Base: 7.2
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H
cvss4
Base: 7.3
Severity: LOW
CVSS:4.0/AV:N/AC:L/AT:N/PR:H/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
Description
A vulnerability has been found in Tenda WH450 1.0.0.18. This impacts an unknown function of the file /goform/PPTPServer. Such manipulation of the argument ip1 leads to stack-based buffer overflow. The attack may be launched remotely. The exploit has been disclosed to the public and may be used.
Risk Information
cvss2
Base: 8.3
Severity: LOW
AV:N/AC:L/Au:M/C:C/I:C/A:C
cvss3
Base: 7.2
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H
cvss4
Base: 7.3
Severity: LOW
CVSS:4.0/AV:N/AC:L/AT:N/PR:H/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
Description
A flaw has been found in omec-project UPF up to 2.1.3-dev. This affects the function handleSessionEstablishmentRequest of the file /pfcpiface/pfcpiface/messages_session.go of the component PFCP Session Establishment Request Handler. This manipulation causes null pointer dereference. The attack may be initiated remotely. The exploit has been published and may be used. The project was informed of the problem early through an issue report but has not responded yet.
Risk Information
cvss2
Base: 4.0
Severity: LOW
AV:N/AC:L/Au:S/C:N/I:N/A:P
cvss3
Base: 4.3
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
cvss4
Base: 5.3
Severity: LOW
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
Description
A vulnerability was detected in floooh sokol up to 16cbcc864012898793cd2bc57f802499a264ea40. The impacted element is the function _sg_pipeline_desc_defaults in the library sokol_gfx.h. The manipulation results in stack-based buffer overflow. The attack requires a local approach. The exploit is now public and may be used. This product does not use versioning. This is why information about affected and unaffected releases are unavailable. The patch is identified as 5d11344150973f15e16d3ec4ee7550a73fb995e0. It is advisable to implement a patch to correct this issue.
Risk Information
cvss2
Base: 4.3
Severity: LOW
AV:L/AC:L/Au:S/C:P/I:P/A:P
cvss3
Base: 5.3
Severity: LOW
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L
cvss4
Base: 4.8
Severity: LOW
CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
References
- https://github.com/floooh/sokol/commit/5d11344150973f15e16d3ec4ee7550a73fb995e0
- https://github.com/floooh/sokol/issues/1405
- https://github.com/floooh/sokol/issues/1406#issuecomment-3649548096
- https://github.com/oneafter/1212/blob/main/hbf1
- https://vuldb.com/?ctiid.338533
- https://vuldb.com/?id.338533
- https://vuldb.com/?submit.719823
Description
A security vulnerability has been detected in PbootCMS up to 3.2.12. The affected element is the function get_user_ip of the file core/function/handle.php of the component Header Handler. The manipulation of the argument X-Forwarded-For leads to use of less trusted source. The attack can be initiated remotely. The exploit has been disclosed publicly and may be used.
Risk Information
cvss2
Base: 5.0
Severity: LOW
AV:N/AC:L/Au:N/C:N/I:P/A:N
cvss3
Base: 5.3
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:N
cvss4
Base: 5.5
Severity: LOW
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
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RapidWhat Do We Measure ?
Incident
Finding
Grade
Digital Assets
Every week, Rankiteo analyzes billions of signals to give organizations a sharper, faster view of emerging risks. With deeper, more actionable intelligence at their fingertips, security teams can outpace threat actors, respond instantly to Zero-Day attacks, and dramatically shrink their risk exposure window.
These are some of the factors we use to calculate the overall score:
Network Security
Identify exposed access points, detect misconfigured SSL certificates, and uncover vulnerabilities across the network infrastructure.
SBOM (Software Bill of Materials)
Gain visibility into the software components used within an organization to detect vulnerabilities, manage risk, and ensure supply chain security.
CMDB (Configuration Management Database)
Monitor and manage all IT assets and their configurations to ensure accurate, real-time visibility across the company's technology environment.
Threat Intelligence
Leverage real-time insights on active threats, malware campaigns, and emerging vulnerabilities to proactively defend against evolving cyberattacks.
Rankiteo is a unified scoring and risk platform that analyzes billions of signals weekly to help organizations gain faster, more actionable insights into emerging threats. Empowering teams to outpace adversaries and reduce exposure.
