Company Details
flock-safety
1,304
75,496
92219
flocksafety.com
477
FLO_2285592
Completed

Flock Safety Company CyberSecurity Posture
flocksafety.comWe are the first public safety operating system empowering thousands of cities to eliminate crime. Our cameras and devices detect objective evidence, decode it with machine learning, and deliver it into the hands that stop crime.
Company Details
flock-safety
1,304
75,496
92219
flocksafety.com
477
FLO_2285592
Completed
Between 650 and 699

Flock Safety Global Score (TPRM)XXXX

Description: A data breach in **Flock Safety’s** camera software—widely deployed by law enforcement—resulted in unauthorized sharing of license plate and vehicle imagery with **federal immigration agencies** through pilot programs. While the breach did not affect the **Normal Police Department (Central Illinois)**, which adheres to the **Illinois Trust Act** (prohibiting non-criminal data sharing), other participating agencies inadvertently exposed data intended for combating **human trafficking and fentanyl distribution** to immigration enforcement. The leak stemmed from **lack of access protocols** in Flock Safety’s system, prompting the company to **pause all federal data-sharing pilots**.The compromised data includes **license plate records and vehicle images**, collected en masse by police departments. Although no direct financial or identity theft was reported, the breach raises concerns over **privacy violations**, **misuse of surveillance data**, and **potential targeting of undocumented individuals**. Flock Safety’s CEO acknowledged systemic gaps, while affected agencies face scrutiny over compliance with data-sharing laws. Periodic audits by departments like Normal PD aim to mitigate risks, but the incident highlights vulnerabilities in **third-party law enforcement tech partnerships** and the **unintended repurposing of surveillance data** for immigration enforcement.
Description: Flock Safety's AI-powered gunshot detection technology, piloted in San Jose, initially had a 50 percent accuracy rate with 34 percent false positives. After recalibration, accuracy improved to 81 percent with 7 percent false alarms. Communities of color expressed concerns about the potential dangers of police responses to false alerts. The technology's reliability is crucial as false positives can lead to unnecessary police dispatch, impacting trust and safety. San Jose's transparency with accuracy data contrasts with the typically opaque reporting of such technology's performance.
Description: Flock Safety's AI-powered gunshot detection technology implemented in San Jose has been reported to yield a high rate of false positives, incorrectly flagging sounds such as fireworks or cars backfiring as gunfire. Initially, only 50 percent of the detected incidents were confirmed as gunshots. After recalibration, accuracy improved, suggesting that such systems may not be as reliable as claimed. The system's potential to dispatch police to non-threatening situations raises concerns, especially in communities of color, about the risks of unnecessary police confrontations.


Flock Safety has 0.0% fewer incidents than the average of same-industry companies with at least one recorded incident.
Flock Safety has 56.25% more incidents than the average of all companies with at least one recorded incident.
Flock Safety reported 1 incidents this year: 0 cyber attacks, 0 ransomware, 0 vulnerabilities, 1 data breaches, compared to industry peers with at least 1 incident.
Flock Safety cyber incidents detection timeline including parent company and subsidiaries

We are the first public safety operating system empowering thousands of cities to eliminate crime. Our cameras and devices detect objective evidence, decode it with machine learning, and deliver it into the hands that stop crime.


TÜV SÜD is the trusted partner of choice for safety, security and sustainability solutions. Our community of experts is passionate about technology and united by the belief that technology should better people’s lives. We work alongside our customers to anticipate and capitalize on technological d

A Guarda Nacional Republicana é uma força de segurança de natureza militar, que tem por missão, no âmbito dos sistemas nacionais de segurança e proteção, assegurar a legalidade democrática, garantir a segurança interna e os direitos dos cidadãos, bem como colaborar na execução da polít
DNV is the independent expert in risk management and assurance, operating in more than 100 countries. Through its broad experience and deep expertise DNV advances safety and sustainable performance, sets industry benchmarks, and inspires and invents solutions. Whether assessing a new ship design,

Neutral, independent third party For more than 150 years, TÜV Rheinland has stood for ensuring quality, safety, and efficiency in conjunction with people, the environment, and technology. As a neutral, independent third party, we test, accompany, develop, promote and certify products, plants, proc

For 100 years, DEKRA has been a trusted name in safety. Founded in 1925 with the original goal of improving road safety through vehicle inspections, DEKRA has grown to become the world's largest independent, non-listed expert organization in the field of testing, inspection, and certification. Today
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A researcher said he was quickly able to take control of a device. A cybersecurity content creator said he found a police login for an...
The City of Woodburn has suspended the use of the Flock Safety Camera System for at least 60 days.
In a near-unanimous vote last night, the Verona Common Council decided against renewing the city's contracts with Flock Safety – a...
In a recent letter to the Federal Trade Commission, Oregon Senator Ron Wyden, called for an investigation of Flock Safety and its data...
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The city of Lakeland currently has 27 automatic license plate reader cameras. Here's what that means for you, LPD and privacy in public...
Flock Safety has contracts spanning more than 5000 police departments, 1000 private companies, and numerous homeowner associations across 49...
Flock Safety—the surveillance company behind the country's largest network of automated license plate readers (ALPRs)—currently faces...

Explore insights on cybersecurity incidents, risk posture, and Rankiteo's assessments.
The official website of Flock Safety is https://www.flocksafety.com/.
According to Rankiteo, Flock Safety’s AI-generated cybersecurity score is 683, reflecting their Weak security posture.
According to Rankiteo, Flock Safety currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.
According to Rankiteo, Flock Safety is not certified under SOC 2 Type 1.
According to Rankiteo, Flock Safety does not hold a SOC 2 Type 2 certification.
According to Rankiteo, Flock Safety is not listed as GDPR compliant.
According to Rankiteo, Flock Safety does not currently maintain PCI DSS compliance.
According to Rankiteo, Flock Safety is not compliant with HIPAA regulations.
According to Rankiteo,Flock Safety is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.
Flock Safety operates primarily in the Public Safety industry.
Flock Safety employs approximately 1,304 people worldwide.
Flock Safety presently has no subsidiaries across any sectors.
Flock Safety’s official LinkedIn profile has approximately 75,496 followers.
Flock Safety is classified under the NAICS code 92219, which corresponds to Other Justice, Public Order, and Safety Activities.
Yes, Flock Safety has an official profile on Crunchbase, which can be accessed here: https://www.crunchbase.com/organization/flock-safety.
Yes, Flock Safety maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/flock-safety.
As of December 02, 2025, Rankiteo reports that Flock Safety has experienced 3 cybersecurity incidents.
Flock Safety has an estimated 2,027 peer or competitor companies worldwide.
Incident Types: The types of cybersecurity incidents that have occurred include Vulnerability, Cyber Attack and Breach.
Detection and Response: The company detects and responds to cybersecurity incidents through an remediation measures with algorithm recalibration, and remediation measures with recalibration of technology, and communication strategy with transparency with accuracy data, and containment measures with paused all pilot data-sharing programs with federal agencies, and remediation measures with review and implementation of data-sharing protocols, and communication strategy with public statement by flock safety ceo garrett langley, communication strategy with media statements by normal police department pio brad park, and enhanced monitoring with periodical audits to ensure compliance with data-sharing policies (normal pd)..
Title: Flock Safety's Gunshot Detection System False Positives
Description: Flock Safety's AI-powered gunshot detection technology implemented in San Jose has been reported to yield a high rate of false positives, incorrectly flagging sounds such as fireworks or cars backfiring as gunfire. Initially, only 50 percent of the detected incidents were confirmed as gunshots. After recalibration, accuracy improved, suggesting that such systems may not be as reliable as claimed. The system's potential to dispatch police to non-threatening situations raises concerns, especially in communities of color, about the risks of unnecessary police confrontations.
Type: System Malfunction
Vulnerability Exploited: AI Algorithm Inefficiency
Title: Flock Safety Gunshot Detection Technology Accuracy Issues
Description: Flock Safety's AI-powered gunshot detection technology, piloted in San Jose, initially had a 50 percent accuracy rate with 34 percent false positives. After recalibration, accuracy improved to 81 percent with 7 percent false alarms. Communities of color expressed concerns about the potential dangers of police responses to false alerts. The technology's reliability is crucial as false positives can lead to unnecessary police dispatch, impacting trust and safety. San Jose's transparency with accuracy data contrasts with the typically opaque reporting of such technology's performance.
Type: Technology Accuracy Issue
Common Attack Types: The most common types of attacks the company has faced is Breach.

Systems Affected: Gunshot Detection System
Operational Impact: High Rate of False Positives
Brand Reputation Impact: Concerns about ReliabilityPotential Risks to Communities of Color

Systems Affected: Gunshot Detection Technology
Operational Impact: Unnecessary Police DispatchImpact on Trust and Safety
Customer Complaints: ['Concerns from Communities of Color']
Commonly Compromised Data Types: The types of data most commonly compromised in incidents are License Plate Images, Vehicle Location Data and .

Entity Name: Flock Safety
Entity Type: Company
Industry: Technology
Location: San Jose

Entity Name: Flock Safety
Entity Type: Company
Industry: Technology
Location: San Jose
Customers Affected: Communities of Color

Remediation Measures: Algorithm Recalibration

Remediation Measures: Recalibration of Technology
Communication Strategy: Transparency with Accuracy Data
Prevention of Data Exfiltration: The company takes the following measures to prevent data exfiltration: Algorithm Recalibration, Recalibration of Technology, , Review and implementation of data-sharing protocols, .
Handling of PII Incidents: The company handles incidents involving personally identifiable information (PII) through by paused all pilot data-sharing programs with federal agencies and .

Lessons Learned: AI systems may not be as reliable as claimed and can lead to unintended consequences.

Recommendations: Continuous monitoring and recalibration of AI algorithms to improve accuracy and reliability.
Key Lessons Learned: The key lessons learned from past incidents are AI systems may not be as reliable as claimed and can lead to unintended consequences.Importance of clear protocols for data-sharing pilot programs, especially with federal agencies.,Need for robust auditing mechanisms to prevent unauthorized data access.,Legal risks of sharing law enforcement data with immigration agencies without proper safeguards.
Implemented Recommendations: The company has implemented the following recommendations to improve cybersecurity: Continuous monitoring and recalibration of AI algorithms to improve accuracy and reliability..
Additional Resources: Stakeholders can find additional resources on cybersecurity best practices at and Source: 25News NowUrl: https://www.25newsnow.comDate Accessed: 2025.
Communication of Investigation Status: The company communicates the status of incident investigations to stakeholders through Transparency With Accuracy Data, Public Statement By Flock Safety Ceo Garrett Langley and Media Statements By Normal Police Department Pio Brad Park.
Advisories Provided: The company provides the following advisories to stakeholders and customers following an incident: was Public Statements By Flock Safety And Normal Police Department.

Root Causes: Inefficiency in AI Algorithm
Corrective Actions: Recalibration of Algorithm

Root Causes: Initial Low Accuracy, High False Positives,
Corrective Actions: Recalibration Of Technology,
Post-Incident Analysis Process: The company's process for conducting post-incident analysis is described as Periodical Audits To Ensure Compliance With Data-Sharing Policies (Normal Pd), .
Corrective Actions Taken: The company has taken the following corrective actions based on post-incident analysis: Recalibration of Algorithm, Recalibration Of Technology, , Pausing All Federal Data-Sharing Pilots., Reviewing And Strengthening Data-Sharing Policies., Enhancing Audit Procedures (As Demonstrated By Normal Pd)., .
Most Significant Data Compromised: The most significant data compromised in an incident were License plate data, Vehicle images and .
Most Significant System Affected: The most significant system affected in an incident was Gunshot Detection Technology and Flock Safety camera softwarePilot program data-sharing systems.
Containment Measures in Most Recent Incident: The containment measures taken in the most recent incident was Paused all pilot data-sharing programs with federal agencies.
Most Sensitive Data Compromised: The most sensitive data compromised in a breach were Vehicle images and License plate data.
Most Significant Lesson Learned: The most significant lesson learned from past incidents was Legal risks of sharing law enforcement data with immigration agencies without proper safeguards.
Most Significant Recommendation Implemented: The most significant recommendation implemented to improve cybersecurity was Ensure compliance with state laws (e.g., Illinois Trust Act) in all data-sharing agreements., Conduct privacy impact assessments before launching pilot programs with federal agencies., Continuous monitoring and recalibration of AI algorithms to improve accuracy and reliability., Implement stricter access controls and audit trails for data-sharing programs. and Enhance transparency with local agencies and the public regarding data-sharing practices..
Most Recent Source: The most recent source of information about an incident is 25News Now.
Most Recent URL for Additional Resources: The most recent URL for additional resources on cybersecurity best practices is https://www.25newsnow.com .
Current Status of Most Recent Investigation: The current status of the most recent investigation is Ongoing (internal review by Flock Safety; no external investigation mentioned).
Most Recent Stakeholder Advisory: The most recent stakeholder advisory issued was Public statements by Flock Safety and Normal Police Department, .
Most Significant Root Cause: The most significant root cause identified in post-incident analysis was Inefficiency in AI Algorithm, Initial Low AccuracyHigh False Positives, Lack of formal protocols for federal data-sharing pilot programs.Inadequate oversight of data access by federal agencies.Potential misalignment between pilot program goals and legal requirements (e.g., Illinois Trust Act)..
Most Significant Corrective Action: The most significant corrective action taken based on post-incident analysis was Recalibration of Algorithm, Recalibration of Technology, Pausing all federal data-sharing pilots.Reviewing and strengthening data-sharing policies.Enhancing audit procedures (as demonstrated by Normal PD)..
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vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.11.1, vllm has a critical remote code execution vector in a config class named Nemotron_Nano_VL_Config. When vllm loads a model config that contains an auto_map entry, the config class resolves that mapping with get_class_from_dynamic_module(...) and immediately instantiates the returned class. This fetches and executes Python from the remote repository referenced in the auto_map string. Crucially, this happens even when the caller explicitly sets trust_remote_code=False in vllm.transformers_utils.config.get_config. In practice, an attacker can publish a benign-looking frontend repo whose config.json points via auto_map to a separate malicious backend repo; loading the frontend will silently run the backend’s code on the victim host. This vulnerability is fixed in 0.11.1.
fastify-reply-from is a Fastify plugin to forward the current HTTP request to another server. Prior to 12.5.0, by crafting a malicious URL, an attacker could access routes that are not allowed, even though the reply.from is defined for specific routes in @fastify/reply-from. This vulnerability is fixed in 12.5.0.
Angular is a development platform for building mobile and desktop web applications using TypeScript/JavaScript and other languages. Prior to 21.0.2, 20.3.15, and 19.2.17, A Stored Cross-Site Scripting (XSS) vulnerability has been identified in the Angular Template Compiler. It occurs because the compiler's internal security schema is incomplete, allowing attackers to bypass Angular's built-in security sanitization. Specifically, the schema fails to classify certain URL-holding attributes (e.g., those that could contain javascript: URLs) as requiring strict URL security, enabling the injection of malicious scripts. This vulnerability is fixed in 21.0.2, 20.3.15, and 19.2.17.
Gin-vue-admin is a backstage management system based on vue and gin. In 2.8.6 and earlier, attackers can delete any file on the server at will, causing damage or unavailability of server resources. Attackers can control the 'FileMd5' parameter to delete any file and folder.
Portkey.ai Gateway is a blazing fast AI Gateway with integrated guardrails. Prior to 1.14.0, the gateway determined the destination baseURL by prioritizing the value in the x-portkey-custom-host request header. The proxy route then appends the client-specified path to perform an external fetch. This can be maliciously used by users for SSRF attacks. This vulnerability is fixed in 1.14.0.

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