CVE-2025-9836VulnerabilityPublished 2 Sep 2025

CVE-2025-9836: macrozheng mall · Authorization Bypass

Affects macrozheng mallSource CVE Database V5

Not known to be exploited · CVSS 5.3 Medium.

Data as of 26 Oct 2026, 06:26 UTC

CVSS 4.0 base score

5.3Medium

How severe the flaw is on the 0–10 CVSS scale.

EPSS: 0.2% chance of exploitation in 30 days – higher than 22% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

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

Base metrics

Attack Vector: Network
Attack Complexity: Low
Attack Requirements: None
Privileges Required: Low
User Interaction: None
Vulnerable system confidentiality: None
Vulnerable system integrity: Low
Vulnerable system availability: None
Subsequent system confidentiality: None
Subsequent system integrity: None
Subsequent system availability: None

Threat metrics

Exploit Maturity: POC

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Network: The vulnerable system is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: The attacker must take no measurable action to exploit the vulnerability. The attack requires no target-specific circumvention to exploit the vulnerability. An attacker can expect repeatable success against the vulnerable system.
Attack Requirements: None: The successful attack does not depend on the deployment and execution conditions of the vulnerable system. The attacker can expect to be able to reach the vulnerability and execute the exploit under all or most instances of the vulnerability.
Privileges Required: Low: The attacker requires privileges that provide basic capabilities that are typically limited to settings and resources owned by a single low-privileged user. Alternatively, an attacker with Low privileges has the ability to access only non-sensitive resources.
User Interaction: None: The vulnerable system can be exploited without interaction from any human user, other than the attacker.
Vulnerable system confidentiality: None: There is no loss of confidentiality within the Vulnerable System.
Vulnerable system integrity: Low: Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact to the Vulnerable System.
Vulnerable system availability: None: There is no impact to availability within the Vulnerable System.
Subsequent system confidentiality: None: There is no loss of confidentiality within the Subsequent System or all confidentiality impact is constrained to the Vulnerable System.
Subsequent system integrity: None: There is no loss of integrity within the Subsequent System or all integrity impact is constrained to the Vulnerable System.
Subsequent system availability: None: There is no impact to availability within the Subsequent System or all availability impact is constrained to the Vulnerable System.
Exploit Maturity: POC: Based on threat intelligence sources each of the following must apply: · Proof-of-concept is publicly available · No knowledge of reported attempts to exploit this vulnerability · No knowledge of publicly available solutions used to simplify attempts to exploit the vulnerability

Definitions: FIRST CVSS v4.0 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 2 Sep 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-26.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Affected software

Product	Affected	Fixed in
macrozheng mall	Affected =1.0.0 =1.0.1 =1.0.2 =1.0.3	Fixed in–

AI-suggested

1. Immediate mitigation should include implementing strict server-side validation and authorization checks on the orderId parameter within the paySuccess function to ensure that only authorized users can confirm payment success for their own orders. 2. Employ application-level access controls that verify user identity and order ownership before processing payment confirmations. 3. Monitor application logs and transaction records for unusual or unauthorized payment confirmations, setting up alerts for suspicious activity. 4. If possible, temporarily disable or restrict access to the /order/paySuccess endpoint until a vendor patch is available. 5. Engage with the vendor or community to obtain or develop patches that address this vulnerability. 6. Conduct a thorough audit of recent transactions to identify any potentially fraudulent orders processed due to this vulnerability. 7. Enhance network-level protections such as Web Application Firewalls (WAFs) with custom rules to detect and block suspicious manipulation of orderId parameters. 8. Educate operational teams about this vulnerability and establish incident response plans specific to potential exploitation scenarios. 9. Review and tighten overall e-commerce platform security, including multi-factor authentication for administrative functions and transaction verification workflows.

Description

A vulnerability was found in macrozheng mall up to 1.0.3. This vulnerability affects the function paySuccess of the file /order/paySuccess. The manipulation of the argument orderId results in authorization bypass. The attack can be launched remotely. The exploit has been made public and could be used.

Impact

For European organizations using macrozheng mall versions up to 1.0.3, this vulnerability poses a significant risk to transactional integrity and financial operations. Attackers exploiting this flaw could confirm payments without proper authorization, leading to fraudulent order processing, financial losses, and reputational damage. E-commerce platforms relying on this software may face direct monetary theft or disruption of order fulfillment processes. Additionally, such unauthorized transactions could complicate compliance with European regulations like GDPR and PCI-DSS, especially if customer data or payment processing is involved. The remote and unauthenticated nature of the exploit increases the threat surface, allowing attackers to target organizations without needing insider access. This could be particularly impactful for small to medium-sized enterprises that may lack robust monitoring or incident response capabilities. The absence of known active exploits currently provides a window for mitigation, but the public availability of the exploit code raises the risk of imminent attacks. Organizations may also face indirect impacts such as customer trust erosion and potential legal liabilities stemming from fraudulent transactions.

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 10 Sep 2025, 04:45 UTC

Technical details

References

Community reviews

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