CVE-2025-0616: Panel unauthenticated SQLi enables

CISO Take

CVE-2025-0616 is an unauthenticated SQL injection (CWE-89, CVSS 8.2) in the B2B Netsis Panel — a web-based management interface used in operational and data pipeline environments — allowing any network-reachable attacker to extract sensitive database contents with no credentials required. The attack is low-complexity, requires no user interaction, and delivers high confidentiality impact, making it trivially exploitable with public SQLi tooling. No patch exists and the vendor did not respond to coordinated disclosure; with 479 downstream dependents and 30 prior CVEs in the same package, this reflects persistent, structural security debt in an unmaintained codebase. Immediate action: restrict panel access to VPN or trusted networks only, deploy WAF rules blocking SQL metacharacter sequences, rotate any credentials or API keys stored in the panel's backing database, and audit query logs for UNION or OR-based injection patterns.

Sources: NVD OpenSSF ATLAS

What is the risk?

HIGH risk for any organization with Netsis Panel exposed to the internet or reachable from untrusted segments. CVSS 8.2 reflects a worst-case exposure profile: unauthenticated, network-reachable, low-complexity attack with high confidentiality impact and no scope change required. The absence of a vendor patch and non-response to disclosure means the exposure window is indefinite — there is no safe version to upgrade to as of the publication date. For AI/ML environments, the primary blast radius is unauthorized read access to configuration databases, stored credentials for AI services, and pipeline metadata. The 30-CVE history in the same package is a strong indicator of systemic code quality issues unlikely to self-resolve.

How does the attack unfold?

Reconnaissance

Attacker identifies exposed Netsis Panel instances via internet scanning (Shodan, FOFA) targeting known panel URL patterns and response fingerprints.

AML.T0006

Initial Access

Attacker injects a SQL payload into an unauthenticated panel input parameter, exploiting CWE-89 to bypass application logic and interact directly with the backend database.

AML.T0049

Data Exfiltration

UNION-based or blind SQL injection systematically extracts database contents including credentials, API keys, user accounts, and AI pipeline configuration metadata.

AML.T0025

Lateral Movement to AI Systems

Extracted credentials and API keys are used to authenticate against connected AI/ML services, enabling compromise of model inference endpoints, data pipelines, or cloud AI accounts.

AML.T0036

Reconnaissance

Attacker identifies exposed Netsis Panel instances via internet scanning (Shodan, FOFA) targeting known panel URL patterns and response fingerprints.

AML.T0006

Initial Access

Attacker injects a SQL payload into an unauthenticated panel input parameter, exploiting CWE-89 to bypass application logic and interact directly with the backend database.

AML.T0049

Data Exfiltration

UNION-based or blind SQL injection systematically extracts database contents including credentials, API keys, user accounts, and AI pipeline configuration metadata.

AML.T0025

Lateral Movement to AI Systems

Extracted credentials and API keys are used to authenticate against connected AI/ML services, enabling compromise of model inference endpoints, data pipelines, or cloud AI accounts.

AML.T0036

What systems are affected?

Package	Ecosystem	Vulnerable Range	Patched
Panel	pip	—	No patch
5.7K OpenSSF 6.5 479 dependents Pushed 6d ago 53% patched ~6d to patch Full package profile →

Do you use Panel? You're affected.

How severe is it?

CVSS 3.1

8.2 / 10

EPSS

N/A

Exploitation Status

No known exploitation

Sophistication

Trivial

What is the attack surface?

AV Network

AC Low

PR None

UI None

S Unchanged

C High

I Low

A None

What should I do?

5 steps

IMMEDIATE — Block external access to Netsis Panel; restrict to internal network or VPN only via firewall or reverse-proxy ACLs.
Deploy WAF rules targeting SQLi patterns in panel request parameters: UNION SELECT, OR 1=1, comment sequences (-- and /*), and stacked queries.
Audit backend database access logs for anomalous queries — focus on UNION, WHERE clause anomalies, and unexpected table reads.
Rotate all credentials, API keys, and secrets stored in the panel's backing database as a precaution.
LONG TERM — Evaluate replacing or retiring Netsis Panel entirely; vendor non-response and 30 historical CVEs indicate an unmaintained codebase with no security roadmap. No patch is available and none is expected based on vendor posture.

How is it classified?

Data Extraction Auth Bypass API AML.T0025 - Exfiltration via Cyber Means AML.T0036 - Data from Information Repositories AML.T0049 - Exploit Public-Facing Application

Which compliance frameworks are affected?

This CVE is relevant to:

EU AI Act

Article 9 - Risk management system

ISO 42001

A.6.2.3 - Data security for AI systems A.9.3 - Security of AI system components

NIST AI RMF

GOVERN 6.2 - Organizational risk policies cover AI supply chain

OWASP LLM Top 10

LLM03:2025 - Supply Chain Vulnerabilities

Frequently Asked Questions

What is CVE-2025-0616?

CVE-2025-0616 is an unauthenticated SQL injection (CWE-89, CVSS 8.2) in the B2B Netsis Panel — a web-based management interface used in operational and data pipeline environments — allowing any network-reachable attacker to extract sensitive database contents with no credentials required. The attack is low-complexity, requires no user interaction, and delivers high confidentiality impact, making it trivially exploitable with public SQLi tooling. No patch exists and the vendor did not respond to coordinated disclosure; with 479 downstream dependents and 30 prior CVEs in the same package, this reflects persistent, structural security debt in an unmaintained codebase. Immediate action: restrict panel access to VPN or trusted networks only, deploy WAF rules blocking SQL metacharacter sequences, rotate any credentials or API keys stored in the panel's backing database, and audit query logs for UNION or OR-based injection patterns.

Is CVE-2025-0616 actively exploited?

No confirmed active exploitation of CVE-2025-0616 has been reported, but organizations should still patch proactively.

How to fix CVE-2025-0616?

1. IMMEDIATE — Block external access to Netsis Panel; restrict to internal network or VPN only via firewall or reverse-proxy ACLs. 2. Deploy WAF rules targeting SQLi patterns in panel request parameters: UNION SELECT, OR 1=1, comment sequences (-- and /*), and stacked queries. 3. Audit backend database access logs for anomalous queries — focus on UNION, WHERE clause anomalies, and unexpected table reads. 4. Rotate all credentials, API keys, and secrets stored in the panel's backing database as a precaution. 5. LONG TERM — Evaluate replacing or retiring Netsis Panel entirely; vendor non-response and 30 historical CVEs indicate an unmaintained codebase with no security roadmap. No patch is available and none is expected based on vendor posture.

What systems are affected by CVE-2025-0616?

This vulnerability affects the following AI/ML architecture patterns: ML operational dashboards, Data pipeline management portals, MLOps administrative interfaces, AI infrastructure management panels.

What is the CVSS score for CVE-2025-0616?

CVE-2025-0616 has a CVSS v3.1 base score of 8.2 (HIGH).

What is the AI security impact?

Affected AI Architectures

ML operational dashboardsData pipeline management portalsMLOps administrative interfacesAI infrastructure management panels

MITRE ATLAS Techniques

AML.T0025 Exfiltration via Cyber Means

AML.T0036 Data from Information Repositories

AML.T0049 Exploit Public-Facing Application

Compliance Controls Affected

EU AI Act: Article 9

ISO 42001: A.6.2.3, A.9.3

NIST AI RMF: GOVERN 6.2

OWASP LLM Top 10: LLM03:2025

What are the technical details?

Original Advisory

Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') vulnerability in Teknolojik Center Telecommunication Industry Trade Co. Ltd. B2B - Netsis Panel allows SQL Injection. This issue affects B2B - Netsis Panel: through 20251003. NOTE: The vendor was contacted early about this disclosure but did not respond in any way.

Exploitation Scenario

An attacker conducting internet reconnaissance via Shodan or FOFA identifies an exposed Netsis Panel instance at an organization running AI/ML infrastructure. Using a crafted HTTP request with a SQL injection payload appended to an unauthenticated search or filter parameter, the attacker injects a UNION SELECT statement to enumerate and extract database tables — no login required. Initial targets are credential tables and stored API keys for connected services (cloud inference endpoints, data pipeline orchestrators). With extracted credentials, the attacker pivots to the organization's AI service accounts, enabling potential data pipeline manipulation, model endpoint hijacking, or training dataset exfiltration. The full chain from panel discovery to credential exfiltration is achievable in under 30 minutes using off-the-shelf SQLi tooling such as sqlmap.

Weaknesses (CWE)

CWE-89 Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')

CWE-89 — Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection'): The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. Without sufficient removal or quoting of SQL syntax in user-controllable inputs, the generated SQL query can cause those inputs to be interpreted as SQL instead of ordinary user data.

[Architecture and Design] Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid [REF-1482]. For example, consider using persistence layers such as Hibernate or Enterprise Java Beans, which can provide significant protection against SQL injection if used properly.
[Architecture and Design] If available, use structured mechanisms that automatically enforce the separation between data and code. These mechanisms may be able to provide the relevant quoting, encoding, and validation automatically, instead of relying on the developer to provide this capability at every point where output is generated. Process SQL queries using prepared statements, parameterized queries, or stored procedures. These features should accept parameters or variables and support strong typing. Do not dynamically construct and execute query strings within these features using "exec" or similar functionality, since this may re-introduce the possibility of SQL injection. [REF-867]

Source: MITRE CWE corpus.