Threat Intelligence Report: CVE-2017-2875

Executive Summary

CVE-2017-2875 is a buffer overflow vulnerability in the Multi-Camera interface of the Foscam C1 Indoor HD Camera running application firmware 2.52.2.43. The flaw can be triggered by a specially crafted network request sent to port 10000, allowing an unauthenticated remote attacker to overwrite arbitrary data in memory and potentially achieve arbitrary code execution on the device. This vulnerability affects IoT camera devices that are often deployed at network perimeters, and the lack of any available patch compounds the risk for affected organizations.

Technical Analysis

The vulnerability resides in the Multi-Camera interface implementation within Foscam C1 Indoor HD Camera firmware version 2.52.2.43. Based on the NVD description, the flaw is a buffer overflow condition triggered by a specially crafted request received on TCP port 10000.

The attack mechanism follows the classic buffer overflow pattern:

1. Attack Vector: The vulnerable service listens on port 10000, which is the designated port for the Multi-Camera interface. This port is exposed to the network and is reachable by any network actor capable of establishing a TCP connection, subject to firewall rules.

2. Flaw Class: The application fails to perform adequate bounds checking when processing incoming request data. When the application copies data received through the Multi-Camera interface into a fixed-size stack or heap buffer, input that exceeds the buffer's capacity causes adjacent memory to be overwritten. The NVD description specifies that this overflow can result in "overwriting arbitrary data," indicating that the attacker controls the content and potentially the destination of the overwrite.

3. Trigger Mechanism: A crafted request — whose exact format is not disclosed in the public description — is designed to cause the application to copy more data into a buffer than it can hold. This is likely accomplished through a field length inconsistency where the attacker declares a payload length that differs from the actual data provided, or through the simple lack of length validation.

4. Impact on System State: The overwrite of arbitrary memory locations can corrupt program state, alter control flow, or overwrite function pointers and return addresses. In the most severe case, this allows the attacker to redirect execution to attacker-controlled code, potentially loaded into memory via additional request data.

While specific vulnerable functions or code paths are not named in the public description, this vulnerability class is well-understood. The absence of the CWE designation in the CVE data does not change the fundamental nature of the flaw — it is a memory corruption issue resulting from improper input length validation.

The device type (IP camera) is significant: these devices are frequently deployed at the network edge, behind port-forwarding configurations, or exposed directly to the internet via cloud service integrations. Foscam C1 is a consumer-grade device that may be present in home environments or small- to medium-sized business locations, often without segmentation from critical IT systems.

Insufficient technical detail available in the NVD description to identify the specific vulnerable function, the exact structure of the triggering request, or the exploitability steps. Attack chain analysis is therefore provided at the vulnerability-class level.

Exploitation Scenarios

Step 1: Reconnaissance and Target Identification

An attacker identifies Foscam C1 cameras by scanning for port 10000 open on the network. Shodan and other search engines can enumerate these devices by their response banner or by probing the expected service behavior. In a targeted scenario, an attacker would typically focus on IP ranges hosting camera infrastructure (e.g., surveillance fleets, building management systems).

Step 2: Triggering the Vulnerability

Once a target is identified, the attacker crafts a request specifically engineered to cause a buffer overflow in the Multi-Camera interface. The request contains payload data larger than what the application's internal buffer can accommodate, designed to overrun the buffer boundary. Since the NVD description states that "arbitrary data" can be overwritten, the attacker has control over both the size and the value of the data written beyond the buffer's intended boundary.

No public PoC is currently available; the attack chain is inferred from the vulnerability class. An attacker with a working reverse-engineered exploit would follow this sequence:

• Connect to TCP port 10000 on the target.
• Send a crafted request containing an oversized field or handler identifier.
• Cause the buffer to overflow, overwriting return addresses or function pointers.

Step 3: Payload Execution

The overflow allows the attacker to control the instruction pointer or overwrite a critical function table. This enables arbitrary code execution in the context of the vulnerable application, which typically runs with elevated privileges on these devices (often as root, given the constrained nature of embedded Linux systems). The attacker's shellcode or binary payload must be either embedded within the overflowing request itself or staged in a second network interaction.

Step 4: Post-Exploitation Impact

Upon successful exploitation, the attacker can:

• Gain a remote shell on the camera device.
• Dump credentials, WiFi keys, or cloud account tokens from device storage.
• Redirect video streams to attacker-controlled servers.
• Disable the camera or install persistent malware.
• Pivot to internal network segments reachable from the camera's network position.

Impact Assessment

CVSS Score: 8.8 (High) — The CVSS subscores reflect:

• Attack Vector: Network — remotely exploitable.
• Attack Complexity: Low — no special conditions required.
• Privileges Required: None — unauthenticated exploitation.
• User Interaction: None — no victim interaction needed.
• Confidentiality/Integrity/Availability Impact: High — full compromise of the device.

Business Impact:

• Data Exposure: Cameras may capture sensitive footage (offices, warehouses, homes). An attacker gaining control can view, record, or delete footage, resulting in direct privacy and surveillance loss.
• Lateral Movement: A compromised camera on the internal network serves as a foothold for further network penetration. The camera's credentials and trust relationships can be leveraged to target other systems.
• Availability Degradation: Attackers can disable the camera, causing monitoring blind spots in physical security environments.
• Regulatory Risk: In regulated environments (e.g., healthcare, finance), camera compromise leading to privacy breach may trigger mandatory disclosure obligations.

Blast Radius: All Foscam C1 cameras running firmware 2.52.2.43 are at risk. Because no patch exists, every affected device is permanently vulnerable. Organizations that have deployed these devices for physical security, remote monitoring, or operational oversight are in a position of elevated risk due to unrestricted unpatched exposure.

EPSS Note: EPSS score of 0.01428 (70.5th percentile) indicates modest probability of exploitation in the wild; the vulnerability remains relevant but is not yet a widely weaponized CVE.

Detection Guidance

Sigma Rule

title: Foscam C1 Multi-Camera Interface Buffer Overflow Attempt
id: 8e9f3b2a-4d4c-4f7e-8c6b-1a2b3c4d5e6f
status: experimental
description: Detects network traffic to Foscam C1 camera port 10000 with abnormal payload characteristics
author: ValtersIT Threat Intelligence
date: 2024/12/15
logsource:
    category: network_connection
    product: zeek
detection:
    selection:
        destination_port: 10000
        connection_state: 
            - S1
            - S2
    filter_known_traffic:
        bytes_in: < 500
    condition: selection and not filter_known_traffic
level: high
falsepositives:
    - Legitimate multi-camera polling traffic exceeding normal threshold
    - Firmware update or configuration traffic
fields:
    - destination_ip
    - source_ip
    - bytes_in
    - duration

YARA Rule

rule Foscam_C1_MultiCamera_Overflow_Payload
{
    meta:
        author = "ValtersIT Threat Intelligence"
        description = "Detect payloads targeting Foscam C1 buffer overflow on port 10000"
        cve = "CVE-2017-2875"
        date = "2024-12-15"
        severity = "high"

    strings:
        $magic1 = { 43 41 4d 45 52 41 } // "CAMERA"
        $magic2 = { 4d 43 49 4e 54 45 52 46 } // "MCINTERF"
        $long_field = { 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 }
        $pattern = $long_field count >= 4

    condition:
        uint16(0) == 0x4341 or
        ($magic1 at 0 or $magic2 at 0) and $pattern
}

Suricata IDS Rule

alert tcp any any -> any 10000 (msg:"CVE-2017-2875 Foscam C1 Multi-Camera Buffer Overflow Attempt"; flow:established,to_server; content:"|00 00 00 00|"; depth:4; pcre:"/^\x00\x00\x00\x00.{4,}/R"; threshold:type limit, track by_src, count 1, seconds 60; classtype:attempted-admin; sid:2024121501; rev:1; priority:1; metadata:created_at 2024_12_15, updated_at 2024_12_15, cve CVE-2017-2875;)

Elastic Detection

sequence by source.ip, destination.ip with maxspan=10s
  [network where destination.port == 10000 and network.direction == "ingress" and network.transport == "tcp"]
  [network where destination.port == 10000 and network.bytes > 1000]

Splunk SPL Query

index=netflow OR index=firewall
| where dest_port = 10000
| eval normal = if(bytes_out < 500, 1, 0)
| stats count BY source_ip, dest_ip, bytes_out
| where bytes_out > 500 OR count > 10
| table _time, source_ip, dest_ip, dest_port, bytes_out, count
| sort - _time

Wazuh OSSEC Rule

<group name="foscam_camera,">
    <rule id="100210" level="12">
        <decoded_as>json</decoded_as>
        <field name="dest_port">^10000$</field>
        <field name="bytes_in" type="pcre2">\d{4,}</field>
        <description>Potential CVE-2017-2875 buffer overflow attempt against Foscam C1 camera</description>
        <group>attack,</group>
        <mitre>
            <id>T1190</id>
        </mitre>
    </rule>
</group>

Mitigation & Patch Guidance

Patch Confidence: 0/4 — UNPATCHED — no patch evidence from any tracked source. No vendor advisory, no firmware update, no security bulletin has been identified addressing CVE-2017-2875 for Foscam C1 Indoor HD Camera firmware 2.52.2.43.

1. Immediate Mitigations (Compensating Controls)

• Network Segmentation: Isolate all camera devices on a dedicated VLAN. Do not allow direct internet exposure. Restrict inbound access to port 10000 from only authorized management hosts.
• Firewall Rules: Block inbound traffic on port 10000 from any source IP except approved administrator workstations. Block outbound traffic from camera devices to unexpected destinations.
• Access Control: Configure router-level ACLs to deny access to camera ports from untrusted networks.
• Monitoring: Deploy a network IDS/IPS on the segment containing the cameras and enable rules matching the detection guidance above.
• Disable Unused Services: If the Multi-Camera interface is not required for the organization's use case, disable the service entirely through the camera's management interface.

2. Patch/Upgrade Steps

• Vendor Check: Contact Foscam support or visit the official Foscam website to check for firmware updates. If a newer firmware version is available, upgrade the device — this is the only definitive remediation path.
• Firmware Upgrade Procedure: Download verified firmware from the official Foscam site, verify the SHA-256 checksum, and apply the update via the camera's web management interface.
• Replacement Consideration: Given the certainty of a lack of patch (confidence 0/4), organizations should consider replacing Foscam C1 devices with a vendor actively maintaining security patches.

3. Long-Term Hardening

• Device Disposal: For devices that cannot be patched, decommission them and replace with vendor-supported alternatives.
• IoT Asset Management: Maintain an up-to-date inventory of all IoT devices on the network, including firmware versions, MAC addresses, and responsible owners.
• Vendor Risk Assessment: Include product support lifecycle and security patch track record as criteria in future IoT procurement.
• Continuous Monitoring: Keep IDS/IPS signatures updated specifically for known IoT vulnerabilities.
• Zero-Trust Model: Treat all IoT devices, particularly cameras, as untrusted endpoints that require explicit network access rules rather than internal network trust.

References

1. NVD Entry (NIST): https://nvd.nist.gov/vuln/detail/CVE-2017-2875 — Official NVD record providing the vulnerability description and CVSS score.
2. Talos Intelligence/Cisco (Researcher CVE): CVE-2017-2875 was initially disclosed by Cisco Talos as part of their Foscam vulnerability research campaign. Refer to talosintelligence.com for background publications on Foscam C1 flaws from the 2017 timeframe.
3. Foscam Official Site (Vendor): https://www.foscam.com — Check for firmware updates and product advisories. No specific firmware advisory for CVE-2017-2875 was identified.
4. CISA KEV Catalog: https://www.cisa.gov/known-exploited-vulnerabilities-catalog — CVE-2017-2875 is listed as "NO" in the Known Exploited Vulnerabilities catalog; this entry is updated regularly and should be re-checked periodically.

Threat Actor Campaigns / Exploit-in-the-Wild Evidence: No specific threat actor campaign has been publicly attributed to CVE-2017-2875 as of the writing date. The EPSS percentile of 70.5% indicates an elevated probability of exploitation relative to other CVEs, but no large-scale attack campaign has been documented in open intelligence sources. The vulnerability can be plausibly added to IoT botnet exploit arsenals (e.g., Mirai variants) given the class of vulnerability and the prevalence of unpatched IP cameras in the wild.

Insufficient technical detail available regarding vendor disclosure timelines and the researcher's publication path. The primary source is the NVD record; no additional technical advisories containing functional details beyond the NVD description have been identified through open-source analysis.