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<ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="f8e07e1c-b58d-4af5-a979-0e79b4384063"><ac:parameter ac:name="">Users_1</ac:parameter></ac:structured-macro>When I was a boy and I would see scary things in the news, my mother would say to me, 'Look for the helpers. You will always find people who are helping.'
- Mister Rogers
The scope of the citizenry affected by cybersecurity vulnerabilities has widened considerably in recent years. In the past, one might have argued that only computer users were affected by vulnerabilities and their disclosure: this is no longer the case. Affected users now include those who have smartphones, watch smart TVs, use credit cards or ATMs for banking and/or shopping, drive cars, fly in airplanes, go to the hospital for diagnostic imaging or intravenous medicine, live in houses with smart meters, and so forth. The list goes on to include nearly everyone, and "opting out" is not a viable position for most people to take.
<ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="76d01691-5efb-4fc0-80c4-637043081448"><ac:parameter ac:name="">_Parting_Thoughts</ac:parameter></ac:structured-macro>In an ideal world, software would do exactly what we expect it to do, and nothing we don't want it to do.
In an ideal world, vendors would be receptive to finding out about vulnerabilities in their products, and would recognize the service provided to them by those who find and report problems. They would be motivated to place user safety, privacy, and security at the top of their priorities.
In an ideal world, human communications would be clear to all parties involved. Well-meaning parties would never misunderstand or misinterpret each other's words or intentions. People would always be polite, patient, humble, calm, without guile, and willing to put aside their own interests for those of others.
We do not live in an ideal world.
In the world we find ourselves occupying, software-based systems exhibit complex behaviors, increasingly exceeding the limits of human comprehension [158]. As a society, we have become capable of building things we don't fully understand. The difference between what a thing does and what you expect it to do can lead to uncertainty, confusion, fear, and vulnerability.
But it's not just the technology that falls short of our ideals. It should come as no surprise that humans have diverse emotions and motives. Values differ. Feelings get hurt, people get frustrated. Words are misinterpreted. Incentives promote individual choices that conflict with each other. What's good for the individual is sometimes bad for the collective, and vice-versa.
And so, we're left to muddle through. To confront each day as an opportunity to learn, another chance to improve, and make tomorrow start a little better than yesterday ended. We scan the horizon to reduce surprise. We test for flaws, we probe for weaknesses, and we identify recurring patterns and themes that lead to undesired outcomes. We fix what we can, mitigate what we can't fix, and remain vigilant over what we can't mitigate. We coordinate vulnerability disclosure because we realize we're all in this together.
Thanks for reading.
<ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="097d34c9-0fa1-45e2-b348-92e6aa0658c6"><ac:parameter ac:name="">_Toc489873275</ac:parameter></ac:structured-macro><ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="a3cb3b7f-1eb3-4d0a-a80a-83faedf2c15c"><ac:parameter ac:name="">_Toc533302245</ac:parameter></ac:structured-macro><ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="287c40d5-5e0f-49df-aabb-d2a09af8a3c4"><ac:parameter ac:name="">_Toc475757919</ac:parameter></ac:structured-macro>Appendix A - On the<ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="e374b545-5834-4364-a24a-e92a7aef57c0"><ac:parameter ac:name="">Internet_of_Things_and_Vulnera</ac:parameter></ac:structured-macro><ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="5bed0914-8e16-4e93-a690-f9f3615f1709"><ac:parameter ac:name="">_Toc479938993</ac:parameter></ac:structured-macro> Internet of Things and Vulnerability Analysis
<ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="81ff72c0-defd-4116-899a-49a3cdd5c804"><ac:parameter ac:name="">_IoT_Vulnerability_Discovery_T</ac:parameter></ac:structured-macro><ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="83ea534a-76e3-4e1b-addb-a72d1e1f1d1e"><ac:parameter ac:name="">IoT_Vulnerability_Discovery</ac:parameter></ac:structured-macro><ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="7e5768ad-26cf-4def-bf9f-e46ce3b59962"><ac:parameter ac:name="">_Toc479938994</ac:parameter></ac:structured-macro>This appendix is adapted from two CERT/CC Blog Posts [159] [156].
IoT Vulnerability Discovery
In 2014 CERT performed a study of vulnerability discovery techniques for IoT systems. As we reviewed the literature, we found a number of techniques in common use. Here they are, ranked in approximately descending order of popularity in the research we surveyed:

  1. Reading documentation: This includes product data sheets, protocol specifications, Internet Drafts and RFCs, manufacturer documentation and specs, patents, hardware documentation, support sites, bug trackers, discussion forums, FCC filings, developer documentation, and related information.
  2. Reverse engineering: In most cases, this consists of reverse engineering (RE) binary firmware or other software to understand its function. However, there are instances in which merely understanding a proprietary file format is sufficient to direct further analyses. Hardware RE appears in some research, but has not been as prevalent as RE of software or file formats. As security researchers develop more hardware knowledge and skills (or as individuals with those skills become security researchers) we expect the prevalence of hardware RE to increase in the security literature.
  3. Protocol analysis: Understanding the communication protocols used by a system is vital to identifying remotely exploitable vulnerabilities. This technique can take the form of simply sniffing traffic to find mistrusted input or channels, or reverse engineering a proprietary protocol enough to build a fuzzer for it. Decoding both the syntax and semantics can be important. In wireless systems, this technique can also take the form of using a software defined radio (SDR) to perform signal analysis, which for this purpose is essentially protocol analysis at a lower level of the stack.
  4. Modeling and simulation: Threat modeling from the attacker perspective was mentioned in a handful of papers, as was modeling and simulation of either the system or its protocols for further analysis using mathematical techniques such as game or graph theory.
  5. Fuzzing: Generating randomized input is a common way to test how a system deals with arbitrary input. Fuzzing of network protocols is a common method cited in a number of reports.
  6. Input or traffic generation and spoofing: Unlike fuzzing, spoofing usually consists of constructing otherwise valid input to a system to cause it to exhibit unexpected behavior. Constructing bogus input from a valid or trusted source also falls into this category.
  7. Scanning: Because most IoT are composed of multiple components, each of which may have its own architecture and code base, it is often the case that a researcher can find known vulnerabilities in systems simply by using available vulnerability scanning tools such as Nessus or Metasploit.
  8. Hardware hacking: This technique involves interfacing directly with the electronics at the circuit level. It is a form of physical-level reverse engineering and can include mapping circuits and connecting with JTAG to dump memory state or firmware.
  9. Debugging: This technique uses software-based or hardware-based debuggers. JTAG is a common hardware debugging interface mentioned in many reports.
  10. Writing code: This technique involves developing custom tools to assist with extracting, characterizing, and analyzing data to identify vulnerabilities.
  11. Application of specialized knowledge and skills: In some cases, just knowing how a system works and approaching it with a security mindset is sufficient to find vulnerabilities. Examples include RFID and ModBus.

Many of the techniques listed above are common to vulnerability discovery in the traditional computing and mobile world. However, the low-hanging fruit appears to hang much lower in the IoT than in traditional computing. From a security perspective, even mobile systems have a head start, although they are not as far along as traditional computing platforms. The fact is that many of the vulnerabilities found thus far in IoT would be considered trivial—and rightly so—in the more mature market of servers and desktop computing. Yet the relative scale of the IoT market makes even trivial vulnerabilities potentially risky in aggregate.
IoT Vulnerability Analysis
In our review of recent security research that focused on vulnerability discovery in the Internet of Things, we identified several key differences between IoT and traditional computing and mobile platforms, including

  1. Limited instrumentation: The vulnerability analyst's ability to instrument the system in order to test its security can be limited. Many of the systems comprise embedded devices that are effectively black boxes at the network level. On the surface, this limitation might appear to be beneficial to the security of the system; if it's hard to create an analysis environment, it might be difficult to find vulnerabilities in the system. However, the problem is that while a determined and/or well-resourced attacker can overcome such obstacles and get on with finding vulnerabilities, a lack of instrumentation can make it difficult even for the vendor to adequately test the security of its own products.
  2. Less familiar system architectures: IoT architectures are often different from those most often encountered by the typical vulnerability analyst. In short, ARM is neither x86 nor IA64, and some embedded systems are neither. Although this limitation is trivially obvious at a technical level, many vulnerability researchers and analysts will have to overcome this skill gap if they are to remain effective at finding and remediating vulnerabilities in IoT.
  3. Limited user interfaces: User interfaces on the devices themselves are extremely limited—a few LEDs, maybe some switches or buttons, and that's about it. Thus, significant effort can be required just to provide input or get the feedback needed to perform security analysis work.
  4. Proprietary protocols: The network protocols used above the transport layer are often proprietary. Although the spread of HTTP/HTTPS continues in this space as it has in the traditional and mobile spaces, there are many extant protocols that are poorly documented or wholly undocumented. The effort required to identify and understand higher level protocols, given sometimes scant information about them, can be daunting. Techniques and tools for network protocol inference and reverse engineering can be effective tactics. However, if vendors were more open with their protocol specifications, much of the need for that effort would be obviated.
  5. Lack of updatability: Unlike most other devices (laptops, PCs, smartphones, tablets), many IoT are either non-updateable or require significant effort to update. Systems that cannot be updated become less secure over time as new vulnerabilities are found and novel attack techniques emerge. Because vulnerabilities are often discovered long after a system has been delivered, systems that lack facilities for secure updates once deployed present a long-term risk to the networks in which they reside. This design flaw is perhaps the most significant one already found in many IoT, and if not corrected across the board, could lead to years if not decades of increasingly insecure devices acting as reservoirs of infection or as platforms for lateral movement by attackers of all types.
  6. Lack of security tools: Security tools used for prevention, detection, analysis, and remediation in traditional computing systems have evolved and matured significantly over a period of decades. And while in many cases similar concepts apply to IoT, the practitioner will observe a distinct gap in available tools when attempting to secure or even observe such a system in detail. Packet capture and decoding, traffic analysis, reverse engineering and binary analysis, and the like are all transferable as concepts if not directly as tools, yet the tooling is far weaker when you get outside of the realm of Windows and Unix-based (including OSX) operating systems running on x86/IA64 architectures.
  7. Vulnerability scanning tool and database bias: Vulnerability scanning tools largely look for known vulnerabilities. They, in turn, depend on vulnerability databases for their source material. However, databases of known vulnerabilities—CVE [14], the National Vulnerability Database (NVD) [150], Japan Vulnerability Notes (JVN) [160] and the CERT Vulnerability Notes Database [15] to name a few—are heavily biased by their history of tracking vulnerabilities in traditional computing systems (e.g., Windows, Linux, OSX, Unix and variants). Recent conversations with these and other vulnerability database operators indicate that the need to expand coverage into IoT is either a topic of active investigation and discussion or a work already in progress. However, we can expect the existing gap to remain for some time as these capabilities ramp up.

  8. Inadequate threat models: Overly optimistic threat models are de rigueur among IoT. Many IoT are developed with what can only be described as naive threat models that drastically underestimate the hostility of the environments into which the system will be deployed. (Undocumented threat models are still threat models, even if they only exist in the assumptions made by the developer.) Even in cases where the developer of the main system is security-knowledgeable, he or she often is composing systems out of components or libraries that may not have been developed with the same degree of security consideration. This weakness is especially pernicious in power- or bandwidth-constrained systems where the goal of providing lightweight implementations supersedes the need to provide a minimum level of security. We believe this is a false economy that only defers a much larger cost when the system has been deployed, vulnerabilities are discovered, and remediation is difficult.
  9. Third-party library vulnerabilities: We observe pervasive use of third-party libraries with neither recognition of nor adequate planning for how to fix or mitigate the vulnerabilities they inevitably contain. When a developer embeds a library into a system, that system can inherit vulnerabilities subsequently found in the incorporated code. Although this is true in the traditional computing world, it is even more concerning in contexts where many libraries wind up as binary blobs and are simply included in the firmware as such. Lacking the ability to analyze this black box code either in manual source code reviews or using most code analysis tools, vendors may find it difficult to examine the code's security.
  10. Unprepared vendors: Often we find that IoT vendors are not prepared to receive and handle vulnerability reports from outside parties, such as the security researcher community. Many also lack the ability to perform their own vulnerability discovery within their development lifecycle. These difficulties tend to arise from one of two causes:
  11. The vendor is comparatively small or new and has yet to form a product security incident response capability.
  12. The vendor has deep engineering experience in its domain but has not fully incorporated the effect of network-enabling its devices into its engineering quality assurance (this is related to the inadequate threat model point above).

Typically, vendors in the latter group may have very strong skills in safety engineering or regulatory compliance, yet their internet security capability is lacking. Our experience is that many IoT vendors are surprised by the vulnerability disclosure process. We frequently find ourselves having conversations that rehash two decades of vulnerability coordination and disclosure debates with vendors who appear to experience something similar to the Kübler-Ross stages of grief The Kübler-Ross stages of grief are denial, anger, bargaining, depression, and acceptance. See http://www.ekrfoundation.org/ during the process.

  1. Unresolved vulnerability disclosure debates: If we have learned anything in decades of CVD at the CERT/CC, it is that there is no single right answer to most vulnerability disclosure questions. However, in the traditional computing arena, most vendors and researchers have settled into a reasonable rhythm of allowing the vendor some time to fix vulnerabilities prior to publishing a vulnerability report more widely. Software as a service (SAAS) and software distributed through app stores can often fix and deploy patches to most customers quickly. On the opposite end of the spectrum, we find many IoT and embedded device vendors for whom fixing a vulnerability might require a firmware upgrade or even physical replacement of affected devices. This diversity of requirements forces vendors and researchers alike to reconsider their expectations with respect to the timing and level of detail provided in vulnerability reports based on the systems affected. Coupled with the proliferation of IoT vendors who are relative novices at internet-enabled devices and just becoming exposed to the world of vulnerability research and disclosure, the shift toward IoT can be expected to reinvigorate numerous disclosure debates as the various stakeholders work out their newfound positions.

IoT Parting Thoughts
Although vulnerability analysis for IoT has much in common with security research in traditional computing and mobile environments, there are a number of important distinctions outlined in this appendix. The threats posed by these systems given their current proliferation trajectory are concerning.
Even as they become more common, it can be difficult to identify the threats posed to a network by IoT either alone or in aggregate. In the simplest sense one might think of it as a "hidden Linux" problem: How many devices can you find in your immediate vicinity containing some form of Linux? Do you know what their patch status is? Do you know how you'd deal with a critical vulnerability affecting them? Furthermore, while the hidden Linux problem isn't going away any time soon, we believe the third-party library problem will long outlast it. How many vulnerable image parsers with a network-accessible attack vector share your home with you? How would you patch them?
Dan Geer [157] puts it thus:
[A]n advanced persistent threat, one that is difficult to discover, difficult to remove, and difficult to attribute, is easier in a low-end monoculture, easier in an environment where much of the computing is done by devices that are deaf and mute once installed or where those devices operate at the very bottom of the software stack, where those devices bring no relevant societal risk by their onesies and twosies, but do bring relevant societal risk at today's extant scales much less the scales coming soon.
We agree.

<ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="1312ef42-f571-41dd-9823-0b0de1f25e30"><ac:parameter ac:name="">_Toc489873276</ac:parameter></ac:structured-macro>Appendix B - Traffic Light Protocol
This appendix is reproduced from https://www.first.org/tlp [140].
FIRST Standards Definitions and Usage Guidance — Version 1.0
1. Introduction

  1. The Traffic Light Protocol (TLP) was created in order to facilitate greater sharing of information. TLP is a set of designations used to ensure that sensitive information is shared with the appropriate audience. It employs four colors to indicate expected sharing boundaries to be applied by the recipient(s). TLP only has four colors; any designations not listed in this standard are not considered valid by FIRST.
  2. TLP provides a simple and intuitive schema for indicating when and how sensitive information can be shared, facilitating more frequent and effective collaboration. TLP is not a "control marking" or classification scheme. TLP was not designed to handle licensing terms, handling and encryption rules, and restrictions on action or instrumentation of information. TLP labels and their definitions are not intended to have any effect on freedom of information or "sunshine" laws in any jurisdiction.
  3. TLP is optimized for ease of adoption, human readability and person-to-person sharing; it may be used in automated sharing exchanges, but is not optimized for that use.
  4. TLP is distinct from the Chatham House Rule (when a meeting, or part thereof, is held under the Chatham House Rule, participants are free to use the information received, but neither the identity nor the affiliation of the speaker(s), nor that of any other participant, may be revealed), but may be used in conjunction if it is deemed appropriate by participants in an information exchange.
  5. The source is responsible for ensuring that recipients of TLP information understand and can follow TLP sharing guidance.
  6. If a recipient needs to share the information more widely than indicated by the original TLP designation, they must obtain explicit permission from the original source.

2. Usage

  1. How to use TLP in email: TLP-designated email correspondence should indicate the TLP color of the information in the Subject line and in the body of the email, prior to the designated information itself. The TLP color must be in capital letters: TLP:RED, TLP:AMBER, TLP:GREEN, or TLP:WHITE.
  2. How to use TLP in documents: TLP-designated documents should indicate the TLP color of the information in the header and footer of each page. To avoid confusion with existing control marking schemes, it is advisable to right-justify TLP designations. The TLP color should appear in capital letters and in 12-point type or greater.

RGB:
 TLP:RED : R=255, G=0, B=51, background: R=0, G=0, B=0
 TLP:AMBER : R=255, G=192, B=0, background: R=0, G=0, B=0
 TLP:GREEN : R=51, G=255, B=0, background: R=0, G=0, B=0
 TLP:WHITE : R=255, G=255, B=255, background: R=0, G=0, B=0
CMYK: TLP:RED : C=0, M=100, Y=79, K=0, background: C=0, M=0, Y=0, K=100
 TLP:AMBER : C=0, M=25, Y=100, K=0, background: C=0, M=0, Y=0, K=100
 TLP:GREEN : C=79, M=0, Y=100, K=0, background: C=0, M=0, Y=0, K=100
 TLP:WHITE : C=0, M=0, Y=0, K=0, background: C=0, M=0, Y=0, K=100
3. TLP definitions

  1. TLP:RED = Not for disclosure, restricted to participants only.

Sources may use TLP:RED when information cannot be effectively acted upon by additional parties and could lead to impacts on a party's privacy, reputation, or operations if misused. Recipients may not share TLP:RED information with any parties outside of the specific exchange, meeting, or conversation in which it was originally disclosed. In the context of a meeting, for example, TLP:RED information is limited to those present at the meeting. In most circumstances, TLP:RED should be exchanged verbally or in person.

  1. TLP:AMBER = Limited disclosure, restricted to participants' organizations.

Sources may use TLP:AMBER when information requires support to be effectively acted upon, yet carries risks to privacy, reputation, or operations if shared outside of the organizations involved. Recipients may only share TLP:AMBER information with members of their own organization, and with clients or customers who need to know the information to protect themselves or prevent further harm. Sources are at liberty to specify additional intended limits of the sharing; these must be adhered to.

  1. TLP:GREEN = Limited disclosure, restricted to the community.

Sources may use TLP:GREEN when information is useful for the awareness of all participating organizations as well as with peers within the broader community or sector. Recipients may share TLP:GREEN information with peers and partner organizations within their sector or community, but not via publicly accessible channels. Information in this category can be circulated widely within a particular community. TLP:GREEN information may not be released outside of the community.

  1. TLP:WHITE = Disclosure is not limited.

Sources may use TLP:WHITE when information carries minimal or no foreseeable risk of misuse, in accordance with applicable rules and procedures for public release. Subject to standard copyright rules, TLP:WHITE information may be distributed without restriction.
Notes:
1. This document uses "should" and "must" as defined by RFC-2119.
2. Comments or suggestions on this document can be sent to tlp-sig@first.org.
<ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="602621af-813e-4732-910f-aa1f187538a4"><ac:parameter ac:name="">_Toc489873277</ac:parameter></ac:structured-macro>Appendix C - Sample Vulnerability Report Form
This is a vulnerability report, typically sent from a reporter to a vendor. These reports may also be shared among other third parties, by the reporter, the vendor, or a coordinator.
This is a report example based on the CERT/CC's Vulnerability Reporting Form [79], and is not meant to be exhaustive of all possibilities. Please modify the sections and format as necessary to better suit your needs.
Vulnerability Report
The information below should be handled as (choose one):
<span style="color: #ff0033">TLP:RED</span> / <span style="color: #ffc000">TLP:AMBER</span> / <span style="color: #33ff00">TLP:GREEN</span> / <span style="color: #ffffff">TLP: WHITE</span>
Vulnerability

  • Software/Product(s) containing the vulnerability:
  • Vulnerability Description:
  • How may an attacker exploit this vulnerability? (Proof of Concept):
  • What is the impact of exploiting this vulnerability? (What does an attacker gain that the attacker didn't have before?)
  • How did you find the vulnerability? (Be specific about tools and versions you used.)
  • When did you find the vulnerability?

Disclosure Plans

  • I have already reported this vulnerability to the following vendors and organizations:
  • Is this vulnerability being publicly discussed? YES/NO, if yes then provide URL.
  • Is there evidence that this vulnerability is being actively exploited? YES/NO, if yes, then provide URL/evidence.
  • I plan to publicly disclose this vulnerability...
  • on this date: (Please include your time zone.)
  • at this URL:

Reporter

  • Name:
  • Organization:
  • Email:
  • PGP Public Key (ASCII Armored or a URL):
  • Telephone:
  • May we provide your contact information to third parties? YES/NO
  • Do you want to be publicly acknowledged in a disclosure? YES/NO

Additional Information

  • Vendor Tracking ID, CERT Tracking ID, or CVE ID if known:
  • Additional Comments:

<ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="474fae8b-b9bb-4b93-8430-3c72007cf8d9"><ac:parameter ac:name="">_Toc489873278</ac:parameter></ac:structured-macro>Appendix D - Sample Vulnerability Disclosure Document
The vulnerability disclosure document is also often referred to as a "security advisory," particularly if published by the vendor.
This is an example of a vulnerability disclosure document based on CERT/CC's Vulnerability Notes [15] format. It is not meant to be exhaustive of all scenarios. Please modify the sections and format as necessary to better suit your needs.
Vulnerability Disclosure Document
Overview

  • Brief Vulnerability Description: (try to keep it to 1-2 sentences)

Vulnerability ID

  • CVE ID for this Vulnerability [14]:

  • Any other IDs (vendor tracking ID, bug tracker ID, CERT ID, etc.):

Description

  • Software/Product(s) containing the vulnerability:
  • Version number of vulnerable software/product:
  • Product Vendor:
  • Type of Vulnerability, if known: (see MITRE's CWE page [77] for list of common types of vulnerabilities)

  • Vulnerability Description:
  • How may an attacker exploit this vulnerability? (Proof of Concept):

Impact

  • What is the impact of exploiting this vulnerability? (What does an attacker gain that the attacker didn't have before?)

CVSS Score

  • CVSS:3.0/AV:?/AC:?/PR:?/UI:?/S:?/C:?/I:?/A:? – 0.0 (LOW/MEDIUM/HIGH/CRITICAL)
  • (Provide the full CVSS vector, not only the score. If possible, provide guidance on the temporal and environmental metrics, not only the base metrics [80].)

Resolution

  • Version containing the fix:
  • URL or contact information to obtain the fix:
  • Alternately, if no fix is available, list workaround or mitigation advice below:

 
Reporter
This vulnerability was reported/discovered by _____________.
Author and/or Contact Info
For more information or questions, please contact:

  • Name:
  • Organization:
  • Email:
  • PGP Public Key (ASCII Armored or a URL):

Disclosure Timeline

  • Date of First Vendor Contact Attempt:
  • Date of Vendor Response:
  • Date of Patch Release:
  • Disclosure Date:

(List more dates here as necessary to document your communication attempts.)
References
(List reference URLs here: for example, vendor advisory, other disclosures, and links to advice on mitigating problems.)
Appendix E – Disclosure Policy Templates
NTIA Early Stage Template
The NTIA Early Stage Template focuses on vulnerability disclosure policy development in safety-critical industries, in which the potential for harm directly impacts public safety or causes physical damage (e.g., automobiles or medical devices), but the lessons are easily adaptable by any organization that builds or maintains its own software or systems. A discussion of issues and template policy is included.
https://www.ntia.doc.gov/files/ntia/publications/ntia_vuln_disclosure_early_stage_template.pdf
Open Source Vulnerability Disclosure Framework
BugCrowd and CipherLaw created the Open Source Vulnerability Disclosure Framework, offered under a Creative Commons Attribution 4.0 International License. The framework "is designed to quickly and smoothly prepare your organization to work with the independent security researcher community while reducing the legal risks to researchers and companies." In addition to a policy template "written with both simplicity and legal completeness in mind," a guidance document is provided for setting up a vulnerability disclosure program.
https://github.com/bugcrowd/disclosure-policy
U.S. GSA Vulnerability Disclosure Policy
The United States General Services Administration (GSA)'s Technology Transformation Service (TTS) provides its vulnerability disclosure policy as a public domain resource.
https://github.com/18F/vulnerability-disclosure-policy
ENISA Good Practice Guide on Vulnerability Disclosure
The Good Practice Guide on Vulnerability Disclosure from European Union Agency for Network and Information Security (ENISA) includes an annotated vulnerability disclosure policy template as an Annex.
https://www.enisa.europa.eu/publications/vulnerability-disclosure/at_download/fullReport
US Department of Justice Framework for a Vulnerability Disclosure Program for Online Systems
The United States Department of Justice (DoJ) has published a white paper containing guidance aimed at developing vulnerability disclosure programs for online systems and services. This report makes a point to distinguish online systems and services from "third-party vulnerability disclosure and hands-on—rather than remote—examination of software, devices, or hardware" because of potentially distinct legal issues that may arise.
https://www.justice.gov/criminal-ccips/page/file/983996/download
The aforementioned report is one of many related white papers provided by the DoJ's Computer Crime and Intellectual Property section.
https://www.justice.gov/criminal-ccips/ccips-documents-and-reports
Where to Look for More
Numerous organizations have already posted their vulnerability disclosure policies. A wide variety of these policies can be found by searching the web for "vulnerability disclosure policy," or "vulnerability disclosure program," or by browsing third-party vulnerability disclosure (e.g., bug bounty) service providers' hosted programs. 
Bibliography
URLs are valid as of the publication date of this document.

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Oxford Living Dictionaries (English), "process," [Online]. Available: https://en.oxforddictionaries.com/definition/process. [Accessed 17 May 2017].

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REPORT DOCUMENTATION PAGE





Form ApprovedOMB No. 0704-0188



Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188), Washington, DC 20503.







1. agency use only
(Leave Blank)


2. report date
August 2017



3. report type and dates covered
Final



4. title and subtitle
The CERT® Guide to Coordinated Vulnerability Disclosure





5. funding numbers
FA8721-05-C-0003



6. author(s)
Allen D. Householder
Garret Wassermann
Art Manion
Chris King







7. performing organization name(s) and address(es)
Software Engineering InstituteCarnegie Mellon UniversityPittsburgh, PA 15213





8. performing organization report number
CMU/SEI-2017-SR-022



9. sponsoring/monitoring agency name(s) and address(es)
AFLCMC/PZE/Hanscom Enterprise Acquisition Division 20 Schilling Circle Building 1305 Hanscom AFB, MA 01731-2116





10. sponsoring/monitoring agency report number
n/a



11. supplementary notes







12adistribution/availability statement
Unclassified/Unlimited, DTIC, NTIS





12b distribution code



13.abstract (maximum 200 words)
Security vulnerabilities remain a problem for vendors and deployers of software-based systems alike. Vendors play a key role by providing fixes for vulnerabilities, but they have no monopoly on the ability to discover vulnerabilities in their products and services. Knowledge of those vulnerabilities can increase adversarial advantage if deployers are left without recourse to remediate the risks they pose. Coordinated Vulnerability Disclosure (CVD) is the process of gathering information from vulnerability finders, coordinating the sharing of that information between relevant stakeholders, and disclosing the existence of software vulnerabilities and their mitigations to various stakeholders including the public. The CERT Coordination Center has been coordinating the disclosure of software vulnerabilities since its inception in 1988. This document is intended to serve as a guide to those who want to initiate, develop, or improve their own CVD capability. In it, the reader will find an overview of key principles underlying the CVD process, a survey of CVD stakeholders and their roles, and a description of CVD process phases, as well as advice concerning operational considerations and problems that may arise in the provision of CVD and related services.







s14. subject terms
Coordinated Vulnerability Disclosure, CVD, vulnerability response process, vulnerability report, CERT-CC, CSIRT, PSIRT, software vulnerability, software security





15. number of pages
122



16. price code







17. security classification of report
Unclassified

18.security classification of this page
Unclassified


19. security classification of abstract
Unclassified



20. limitation of abstract
UL

NSN 7540-01-280-5500




Standard Form 298 (Rev. 2-89) Prescribed by ANSI Std. Z39-18 298-102



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