Tenda AC15 15.03.05.18/15.03.05.19/15.03.20 /goform/SetSysTimeCfg fromSetSysTime time stack-based overflow

EntryHistoryDiffrelatejsonxml

CVSS Meta Temp Score CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.	Current Exploit Price (≈) Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.	CTI Interest Score Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
8.9	$0-$5k	0.05

Overview

A vulnerability classified as critical was found in Tenda AC15 15.03.05.18/15.03.05.19/15.03.20. Affected by this vulnerability is the function fromSetSysTime of the file /goform/SetSysTimeCfg. The manipulation of the argument time leads to stack-based buffer overflow. The CWE definition for the vulnerability is CWE-121. The weakness was shared 03/23/2024. It is possible to read the advisory at github.com. This vulnerability is known as CVE-2024-2855. The attack can be launched remotely. Technical details are available. Furthermore, there is an exploit available. The exploit has been disclosed to the public and may be used. The pricing for an exploit might be around USD $0-$5k at the moment. It is declared as proof-of-concept. It is possible to download the exploit at github.com. We expect the 0-day to have been worth approximately $0-$5k. The vendor was contacted early about this disclosure but did not respond in any way. [Details]

IOB - Indicator of Behavior (969)

Timeline

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Lang

en	796
zh	26
de	22
es	22
fr	22

Country

US: USA	156
DE: Germany	150
GB: Great Britain	86
IT: Italy	26
FR: France	22

Actors

Cobalt Strike	5
Sandworm	3
Mirai	2
Quasar RAT	2
Pacha	1

Activities

IOC - Indicator of Compromise (31)

These indicators of compromise highlight associated network ranges which are known to be part of research and attack activities.

ID	IP range	Actor	Type	Confidence
1	3.79.242.0/24	Nanocore RAT	predictive	High
2	3.125.52.0/24	Cobalt Strike	predictive	High
3	8.219.195.0/24	Responder	predictive	High
4	8.219.204.0/24	Cobalt Strike	predictive	High
5	X.XXX.XXX.X/XX	Xxxxxx Xxxxxx	predictive	High
6	X.XXX.XXX.X/XX	Xxxxxx Xxxxxx	predictive	High
7	X.XXX.XXX.X/XX	Xxxxxxx	predictive	High
8	XX.XX.XXX.X/XX	Xxxxx Xxxxx	predictive	High
9	XX.XXX.XXX.X/XX	Xxxxxxx	predictive	High
10	XX.XXX.XX.X/XX	Xxxxx	predictive	High
11	XX.XXX.XX.X/XX	Xxxxx	predictive	High
12	XX.XX.XXX.X/XX	Xxxxxxxx	predictive	High
13	XX.XX.XXX.X/XX	Xxxxxxx	predictive	High
14	XX.XX.XX.X/XX	Xxxxxxx Xxx	predictive	High
15	XX.XXX.XXX.X/XX	Xxxxxx	predictive	High
16	XXX.XX.XX.X/XX	Xxxxxx	predictive	High
17	XXX.XX.XX.X/XX	Xxxxxx	predictive	High
18	XXX.XX.XXX.X/XX	Xxxxxx Xxxxxx	predictive	High
19	XXX.X.XXX.X/XX	Xxxxxx	predictive	High
20	XXX.XXX.XXX.X/XX	Xxxxxxxxxxxx	predictive	High
21	XXX.XX.XXX.X/XX	Xxxxxxx	predictive	High
22	XXX.XXX.XXX.X/XX	Xxxx	predictive	High
23	XXX.XXX.XX.X/XX	Xxxxxxxx	predictive	High
24	XXX.XXX.XXX.X/XX	Xxxx	predictive	High
25	XXX.XXX.XXX.X/XX	Xxxxx Xxxxxxx	predictive	High
26	XXX.XXX.XXX.X/XX	Xxxxxxxx	predictive	High
27	XXX.XXX.XXX.X/XX	Xxxxxxxxx Xxxxxx	predictive	High
28	XXX.XX.XXX.X/XX	Xxxxxx	predictive	High
29	XXX.XX.XXX.X/XX	Xxxxxx Xxxxxx	predictive	High
30	XXX.XXX.XX.X/XX	Xxxxxxxx	predictive	High
31	XXX.XXX.XX.X/XX	Xxxxxxxx	predictive	High

IOA - Indicator of Attack (2)

These indicators of attack list the potential fragments used for technical activities like reconnaissance, exploitation, privilege escalation, and exfiltration. This data is unique as it uses our predictive model for actor profiling.

ID	Class	Indicator	Type	Confidence
1	File	/goform/SetSysTimeCfg	verified	High
2	Argument	xxxx	verified	Low

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