What is the official website of Lacerta Group, LLC. ?

The official website of Lacerta Group, LLC. is http://lacerta.com.

What is Lacerta Group, LLC.'s cybersecurity risk score?

Lacerta Group, LLC. has an AI-generated cybersecurity risk score of 743 out of 1000, indicating a Moderate security posture according to Rankiteo's assessment.

How many security incidents has Lacerta Group, LLC. experienced?

According to Rankiteo, Lacerta Group, LLC. currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has Lacerta Group, LLC. been affected by any supply chain cyber incidents ?

According to Rankiteo, Lacerta Group, LLC. has not been affected by any supply chain cyber incidents, and no incident IDs are currently listed for the organization.

Does Lacerta Group, LLC. have SOC 2 Type 1 certification ?

According to Rankiteo, Lacerta Group, LLC. is not certified under SOC 2 Type 1.

Does Lacerta Group, LLC. have SOC 2 Type 2 certification ?

According to Rankiteo, Lacerta Group, LLC. does not hold a SOC 2 Type 2 certification.

Does Lacerta Group, LLC. comply with GDPR ?

According to Rankiteo, Lacerta Group, LLC. is not listed as GDPR compliant.

Does Lacerta Group, LLC. have PCI DSS certification ?

According to Rankiteo, Lacerta Group, LLC. does not currently maintain PCI DSS compliance.

Does Lacerta Group, LLC. comply with HIPAA ?

According to Rankiteo, Lacerta Group, LLC. is not compliant with HIPAA regulations.

Does Lacerta Group, LLC. have ISO 27001 certification ?

According to Rankiteo,Lacerta Group, LLC. is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.

Which industry does Lacerta Group, LLC. operate in ?

Lacerta Group, LLC. operates primarily in the Packaging and Containers Manufacturing industry.

How many employees does Lacerta Group, LLC. have ?

Lacerta Group, LLC. employs approximately 169 people worldwide.

Does Lacerta Group, LLC. own any subsidiaries ?

Lacerta Group, LLC. presently has no subsidiaries across any sectors.

How many LinkedIn followers does Lacerta Group, LLC. have ?

Lacerta Group, LLC.'s official LinkedIn profile has approximately 2,536 followers.

Does Lacerta Group, LLC. have a Crunchbase profile ?

No, Lacerta Group, LLC. does not have a profile on Crunchbase.

Does Lacerta Group, LLC. have a LinkedIn profile ?

Yes, Lacerta Group, LLC. maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/lacerta-group-inc.

How many cybersecurity incidents has Lacerta Group, LLC. experienced ?

As of June 23, 2026, Rankiteo reports that Lacerta Group, LLC. has experienced 1 cybersecurity incidents.

How many peer or competitor companies does Lacerta Group, LLC. have ?

Lacerta Group, LLC. has an estimated 2,248 peer or competitor companies worldwide.

What types of cybersecurity incidents has Lacerta Group, LLC. faced ?

Incident Types: The types of cybersecurity incidents that have occurred include Ransomware.

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LGL

Boost Score +25 with badge (5 left)

743

/1000

Moderate

768

/1000

Fair

Lacerta Group, LLC. Vendor Cyber Rating & Cyber Score

lacerta.com

Add Your Compliance Badge

Lacerta Group, LLC. has been a leading provider of innovative thermoformed packaging solutions since 1993. Our reputation is built on product integrity, excellent customer service, sustainability, and speed to market. Lacerta provides packaging and storage solutions for food processors and supermarkets. We offer a comprehensive product portfolio of PET packaging, sustainable packaging, and in-house design capabilities. Whatever your needs across the product life cycle, Lacerta’s fully integrated manufacturing platform can help you tackle any packaging challenge. Our capabilities include design and engineering, prototyping, mold-making and tooling, thermoforming, extrusion, and printing in our own facilities. Our customers drive our

LGL A.I CyberSecurity Scoring

Scoring History

LGL

Lacerta Group, LLC. CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

Lacerta Group, LLC.

Ransomware

100

8/2021

SI-553072525

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A.I.

LGL Company Scoring based on AI Models

Cyber Incidents Likelihood 3 - 6 - 9 months

Actual

Prediction

Incident Predictions locked

Access Monitoring Plan

A.I Risk Score Likelihood 3 - 6 - 9 months

Actual

Prediction A

Prediction B

Prediction C

Prediction D

A.I. Risk Score Predictions locked

Access Monitoring Plan

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Underwriter Stats for LGL

Incidents vs Packaging and Containers Manufacturing Industry Avg (This Year)

No incidents recorded for Lacerta Group, LLC. in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Lacerta Group, LLC. in 2026.

Incident Types LGL vs Packaging and Containers Manufacturing Industry Avg (This Year)

No incidents recorded for Lacerta Group, LLC. in 2026.

Incident History - LGL (X = Date, Y = Severity)

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SUBSIDIARY

Lacerta Group, LLC. Subsidiaries

LGL

Packaging and Containers Manufacturing

Website: http://lacerta.com

Company Size: 169

SK Capital PartnersFinancial Services

Apotex Inc.Pharmaceutical Manufacturing

Apotex Pharmachem Inc.Pharmaceutical Manufacturing

ApobiologixBiotechnology Research

Apotex Inc. - QuébecPharmaceutical Manufacturing

HeubachChemical Manufacturing

SEQENSPharmaceutical Manufacturing

SEQENS Pharmaceutical SolutionsPharmaceutical Manufacturing

SEQENS Personal CarePersonal Care Product Manufacturing

ArchromaChemical Manufacturing

Color Atlas by ArchromaTextilherstellung

SI GroupChemical Manufacturing

Careers at SI GroupChemical Manufacturing

Ascend Performance MaterialsChemical Manufacturing

Acteev By AscendTextile Manufacturing

Valtris Specialty ChemicalsChemical Manufacturing

TPC GroupChemical Manufacturing

Isolatek InternationalWholesale Building Materials

GEON Performance SolutionsPlastics Manufacturing

EcopolPackaging and Containers Manufacturing

Tilley DistributionChemical Manufacturing

Noramco™Pharmaceutical Manufacturing

Luxium SolutionsManufacturing

DeltechChemical Manufacturing

INEOS CalabrianChemical Manufacturing

Foremark Performance ChemicalsChemical Manufacturing

Woodstock Sterile SolutionsPharmaceutical Manufacturing

J&K IngredientsFood and Beverage Manufacturing

Florachem CorporationChemical Manufacturing

VanDeMark Chemical IncChemical Manufacturing

CanlakChemical Manufacturing

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Tetra Pak

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We’re here to make food safe and available. It’s why we provide advanced food production systems, from product creation and recipe testing to processing, filling, packaging, logistics, services and beyond. We support almost every food and beverage category with tailored solutions for category-specific needs. In collaboration with our customers and suppliers, driven by more than 24,000 dedicated employees worldwide, we protect food sustainably every day for hundreds of millions of people in more than 160 countries. Because we’re here to fulfil a purpose: We commit to making food safe and available, everywhere, and we promise to protect what’s good: food, people and the planet. LinkedIn Community Guidelines for Tetra Pak As part of our commitment to you we will endeavour to ensure that the content on this page is positive and respectful. In doing so we ask that you respect our LinkedIn page guidelines. These guidelines also apply to all company spokespeople. While we welcome any posts and comments, it’s important to note that postings to the Tetra Pak LinkedIn page, from other users, are not representative of the opinions of Tetra Pak, therefore do we not confirm their accuracy. Since we can't monitor every posting or conversation, we realise that the occasional objectionable post will pop up from time to time. We therefore reserve the right to remove posts or comments that are: - Abusive, defamatory, obscene, or offensive - Fraudulent, deceptive, misleading, or unlawful - Hateful in language targeting race/ethnicity, religion, gender, nationality, or political beliefs - In violation of any intellectual property right - Sales pitches or commercial solicitation - Not being relevant to the topic or content in the post that has been published - Spamming or link baiting

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NEWS

Lacerta Group, LLC. CyberSecurity News

Latest updates, reports, and threat intel affecting the global network.

November 20, 2024 08:00 AM

Inline for a New Trial

Inline Plastics Corp. (“Inline”) filed a lawsuit against Lacerta Group, LLC (“Lacerta”), alleging infringement of several patents related to...

Read Article

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CVE

Latest

Global CVEs (Not Company-Specific)

CVE-2026-54236

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, the fix for CVE-2026-22778, which introduced a sanitize_message helper that strips object-repr memory addresses from error messages before they reach the client, is incomplete: several response paths echo str(exc) directly to clients without calling sanitize_message. The unsanitized sites include the Anthropic API router in vllm/entrypoints/anthropic/api_router.py (the POST /v1/messages and POST /v1/messages/count_tokens handlers), the Server-Sent Events streaming converter in vllm/entrypoints/anthropic/serving.py, and the realtime speech-to-text WebSocket in vllm/entrypoints/speech_to_text/realtime/connection.py. These paths catch the exception inside the route coroutine and construct the JSONResponse themselves, bypassing the sanitizing global FastAPI exception handler, and WebSocket frames do not traverse that handler chain at all. Using the same primitive as the parent issue, an unauthenticated attacker can send malformed image bytes through the Anthropic Messages API image content parts so that PIL.Image.open raises an UnidentifiedImageError whose message contains the BytesIO object repr, leaking the heap memory address verbatim in the error.message field of the response body. This vulnerability is fixed in 0.23.1rc0.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: 5.3)

cvss3

Base Score: 5.3

Complexity: LOW

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N

Impact Score

1.4

Exploitability

3.9

REFERENCES

CVE-2026-54235

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, ll temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. This vulnerability is fixed in 0.23.1rc0.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: )

cvss4

Base Score: 6.9

Complexity: LOW

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:X/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

Impact Score

Exploitability

REFERENCES

CVE-2026-54233

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, vLLM's /v1/audio/transcriptions endpoint limits compressed upload size but not decoded PCM output. A 25MB OPUS file expands to ~14.9GB of float32 PCM at decode time. This vulnerability is fixed in 0.23.1rc0.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: 6.5)

cvss3

Base Score: 6.5

Complexity: LOW

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Impact Score

3.6

Exploitability

2.8

REFERENCES

CVE-2026-54232

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.1, the vLLM Dockerfile is vulnerable to a dependency confusion attack through the flashinfer-jit-cache package. The package is installed from a custom index (flashinfer.ai/whl/) using --extra-index-url, but the package name was not registered on PyPI, and UV_INDEX_STRATEGY="unsafe-best-match" is set globally. An attacker who registers flashinfer-jit-cache on PyPI with version 0.6.11.post2 can execute arbitrary code as root during the Docker build and backdoor every resulting container image, enabling exfiltration of all user prompts, API credentials, and model data from production vLLM deployments This vulnerability is fixed in 0.22.1.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: 8.8)

cvss3

Base Score: 8.8

Complexity: LOW

CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Impact Score

5.9

Exploitability

2.8

REFERENCES

https://github.com/vllm-project/vllm/security/advisories/GHSA-jrf6-vqxq-pjv2

CVE-2026-53923

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). From 0.5.5 until 0.23.1rc0, integer truncation of tensor dimensions in vLLM's GGUF dequantize kernels (csrc/quantization/gguf/gguf_kernel.cu) causes partial tensor processing. The output tensor is allocated at full size via torch::empty (uninitialized memory), but the dequantize CUDA kernel processes only a truncated number of elements. The unfilled portion of the output tensor retains whatever was previously in GPU memory. In multi-tenant inference deployments, this residual GPU memory may contain tensor data from other users' inference requests, constituting information disclosure. This vulnerability is fixed in 0.23.1rc0.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: )

cvss4

Base Score: 5.3

Complexity: LOW

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:L/VI:L/VA:N/SC:N/SI:N/SA:N/E:X/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

Impact Score

Exploitability

REFERENCES

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