CN111708967B - Fingerprint identification method based on sitemap - Google Patents
Fingerprint identification method based on sitemap Download PDFInfo
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- CN111708967B CN111708967B CN202010530722.3A CN202010530722A CN111708967B CN 111708967 B CN111708967 B CN 111708967B CN 202010530722 A CN202010530722 A CN 202010530722A CN 111708967 B CN111708967 B CN 111708967B
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Abstract
The invention discloses a fingerprint identification method based on a sitemap, which comprises the following steps: capturing a sitemap of a target website, and representing the sitemap by using an n-ary tree; pruning the sitemap tree according to the website path blacklist, reserving a website path capable of reflecting website fingerprints, and generating a simplified sitemap tree; establishing a website fingerprint-website map tree bank; traversing a sitemap tree in a sitemap tree bank and matching with a target sitemap tree, thereby obtaining fingerprint information of a target website; and updating the corresponding information of the website fingerprint and the sitemap tree of the target website into a website fingerprint-sitemap tree bank. The invention improves the efficiency and accuracy of acquiring the website fingerprint.
Description
Technical Field
The invention provides a method for carrying out website fingerprint identification on a constructed sitemap, and relates to core technologies and algorithms for filtering the sitemap, carrying out website fingerprint identification on the filtered sitemap and establishing a website fingerprint identification library.
Background
With the rapid development of the mobile internet, the explosive growth of websites is promoted, and meanwhile, the defense system is improved day by day due to the increasing of website defense technology. The security tester can not quickly identify the fingerprint of the website when carrying out security test on the website. On the other hand, the traditional website fingerprint identification has poor stability, and often large errors or incapability of identification are caused by changing the deployment file. Correct and rapid website fingerprinting will help security testers to perform security tests more specifically.
Disclosure of Invention
The invention aims to provide a fingerprint identification method based on a sitemap aiming at the defects of the prior art.
The aim of the invention is realized by the following technical scheme: a sitemap-based fingerprint identification method, the method comprising the steps of:
(1) Generating a sitemap tree: capturing a sitemap of a target website, and representing the sitemap by using an n-ary tree T0;
(2) Pruning the sitemap tree: pruning the sitemap tree T0 according to the website path blacklist, reserving a website path capable of reflecting website fingerprints, and generating a simplified sitemap tree T1;
(3) Establishing a website fingerprint-sitemap tree bank D1;
(4) Fingerprint identification: traversing a sitemap tree in a sitemap tree bank and matching with a target sitemap tree, thereby obtaining fingerprint information of a target website;
(5) Website fingerprint-sitemap tree bank update: and updating the corresponding information of the website fingerprint and the sitemap tree of the target website into a website fingerprint-sitemap tree bank.
Further, each node of the n-ary tree T0 has two attributes: the value val of the current node and the child node list child of the current node.
Further, in the step (2), a blacklist is established for general fields which cannot reflect the characteristics of the website;
when a certain node of the sitemap tree exists in the blacklist, the node is cut off;
when the number of child nodes of a certain node of the sitemap tree is greater than a node threshold, the node is pruned.
Further, in the step (3), the construction method of the website fingerprint-sitemap tree bank specifically comprises the following steps:
establishing a website fingerprint library D0 and storing a plurality of website fingerprints;
establishing a website fingerprint-website map tree library D1, and storing one-to-many relation between the website fingerprint and the website map tree;
for each website fingerprint in D0, finding a website corresponding to the website fingerprint, then obtaining a website map of the website, further obtaining a website map tree of the website, and adding the corresponding information of the website fingerprint-website map tree into D1.
Further, in the step (4), the sitemap tree of the target website is set to be T0, each piece of data in D1 is traversed to obtain the corresponding information of the sitemap-sitemap tree, the currently traversed sitemap is set to be F1, the sitemap tree is set to be T1, and the matching is performed on T0 and T1, and the specific calculation method is as follows:
firstly, traversing the hierarchy T0, comparing val of the traversed node with val of a root node of T1, and if different, continuing traversing downwards; if the two nodes are the same, setting a tree taking the current node as a root node in T0 as T2, and then calculating the similarity between the T2 and the T1;
if the calculated similarity of the T1 and the T2 is higher than the similarity threshold, the T1 and the T2 can be considered to be successfully matched, and the target website can be further confirmed to be matched with the website fingerprint F1; if T1 and T2 can be successfully matched, intercepting T2, reserving nodes within the range of the height H of T1, recording as T3, and recording corresponding information of F1-T3 at the moment;
after the similarity calculation of the T1 and the T2 is completed, continuing to traverse the T0 in a layering way, and circulating the calculation process to finally obtain a group of fingerprints matched by the T0 and the information of a new webpage map tree T3 corresponding to each fingerprint in the group of fingerprints.
Further, in the step (4), the specific method for calculating the similarity between T1 and T2 is as follows:
performing hierarchical traversal from the root node of the T1, comparing the node val between the T1 and the T2 at the same layer, and ending the similarity calculation process after the T1 traversal is completed; recording the depth d of the root node as 0, and increasing the node depth from top to bottom in sequence; in each layer, the similarity of the layer is calculated, and the calculation formula is as follows:
the maximum number of nodes refers to the maximum value of the number of nodes of the layer d of the same depth of T1 and T2;
after the similarity calculation of each layer of depth is completed, summing and marking as sum;
the similarity calculation formula of T1 and T2 is as follows:
further, in the step (5), the fingerprints matched with the target website and the information of the new webpage map tree T3 corresponding to each fingerprint obtained in the step (4) are updated into the website fingerprint-website map tree library, so that the information of the website fingerprint-website map tree library is further expanded, and the coverage of the website fingerprint-website map tree library is increased.
The beneficial effects of the invention are as follows: the method captures the sitemap of the target website and represents the sitemap by using an n-ary tree; pruning the sitemap tree according to the website path blacklist, reserving a website path capable of reflecting website fingerprints, and generating a simplified sitemap tree; establishing a website fingerprint-website map tree bank; traversing a sitemap tree in a sitemap tree bank and matching with a target sitemap tree, thereby obtaining fingerprint information of a target website; and updating the corresponding information of the website fingerprint and the sitemap tree of the target website into a website fingerprint-sitemap tree bank. The invention improves the efficiency and accuracy of acquiring the website fingerprint.
Drawings
FIG. 1 is a flow chart of the sitemap-based fingerprint identification of the present invention;
FIG. 2 is a schematic diagram of an n-ary tree corresponding to a sitemap of hundred degrees;
fig. 3 is a schematic diagram of a simplified matching process of sitemap trees T0, T1.
Detailed Description
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
As shown in fig. 1, the invention provides a sitemap-based fingerprint identification method, which comprises the following steps:
(1) Generating a sitemap tree: capturing a sitemap of a target website, and representing the sitemap by using an n-ary tree T0;
(2) Pruning the sitemap tree: pruning the sitemap tree T0 according to the website path blacklist, reserving a website path capable of reflecting website fingerprints, and generating a simplified sitemap tree T1;
(3) Establishing a website fingerprint-website map tree bank;
(4) Fingerprint identification: traversing a sitemap tree in a sitemap tree bank and matching with a target sitemap tree, thereby obtaining fingerprint information of a target website;
(5) Website fingerprint-sitemap tree bank update: and updating the corresponding information of the website fingerprint and the sitemap tree of the target website into a website fingerprint-sitemap tree bank.
In the step (1), capturing a sitemap of a target website, and representing the sitemap by using an n-ary tree T0, wherein the steps are as follows:
taking the official website of hundred degrees (https:// www.baidu.com /) as an example, the corresponding n-ary tree of the sitemap is shown in FIG. 2. It should be noted that, the sitemap refers to a navigation web page file generated according to the structure, frame and content of the website, any manner of capturing the sitemap of the target website in the prior art may be adopted, which is not limited in the embodiment of the present invention, and a person skilled in the art may select according to needs.
Further, the data structure of the nodes in the n-ary tree is defined as follows:
it can be seen that there are two attributes per node, val represents the value of the current node, and child represents the child node list of the current node.
In step (2), a blacklist is established from general fields which cannot reflect the characteristics of the website, wherein the blacklist comprises, but is not limited to, the following named fields: time, pure numbers, etc.
When a node of the sitemap tree exists in the blacklist, the node is pruned.
When the number of child nodes of a certain node of the sitemap tree is greater than a node threshold (preferably 100), the node is pruned, and a pruned sitemap tree T1 is generated.
In the step (3), the website fingerprint is used for realizing accurate identification of the target web application, and specifically, the target web application is identified in five aspects of application name (version), server software (version), programming language (version), application framework (version) and application component.
The construction method of the website fingerprint-sitemap tree bank specifically comprises the following steps: a website fingerprint library D0 is established to store a plurality of website fingerprints. A sitemap-sitemap tree library D1 is created for storing one-to-many relationships of sitemaps and sitemap trees. Since the establishment of D1 is based on all the website fingerprints existing in D0 to establish a correspondence, the richness of the website fingerprint types in D0 determines the richness of the fingerprint types in D1. Further, in the invention, the identification of the target website fingerprint is realized by comparing the similarity between the website map tree of the target website and the website map tree of the known website fingerprint in D1, so that the more the fingerprint types in D0 are, the more the fingerprint types in D1 are, and the greater the probability of accurately identifying the website fingerprint of the target website is, so that the existing website fingerprint is added as much as possible in the process of establishing D0. After the complete website fingerprint database D0 is built, the website fingerprint-website map tree database D1 is built. In this process, for each website fingerprint in D0, it is necessary to find a typical implementation of a website map tree corresponding to the website fingerprint, and in a specific implementation, first find a website corresponding to the website fingerprint, then obtain a website map of the website, further obtain a website map tree of the website, and then add the corresponding information of the website fingerprint-website map tree to D1. Note here that the implementation of multiple sitemap trees to which the same sitemap may correspond, the correspondence between the sitemap and the sitemap tree is one-to-many.
In the step (4), the matching process of the sitemap tree in the sitemap tree bank and the target sitemap tree is specifically as follows:
and (3) setting the sitemap tree of the target website as T0, traversing each piece of data in D1 to obtain corresponding information of the sitemap-sitemap tree, and setting the currently traversed sitemap as F1 and the sitemap tree as T1. Then, starting with the matching of T0, T1, the simplified sitemap tree T0, T1 of fig. 3 is taken as an example, where nodes in the sitemap tree are also shown in simplified form, in order to more clearly describe the matching process. The specific calculation method is as follows:
firstly, traversing the hierarchy T0, comparing val of the traversed node with val of a root node of T1, and if different, continuing traversing downwards; if the two nodes are the same, setting a tree taking the current node as a root node in T0 as T2, and then calculating the similarity between T2 and T1. In fig. 3, when traversing to the node b in T0, the condition is satisfied, where T2 is T2 shown in fig. 2, and a specific method for calculating the similarity of T1 and T2 is:
first the height of T1 is calculated and denoted as H. Then, from the root node of T1, namely node b, hierarchical traversal is started, comparison of node val between T1 and T2 is performed at the same layer, and after the traversal of T1 is completed, the similarity calculation process is ended. The depth d of the root node is 0, and the node depth is sequentially increased from top to bottom. In each layer, the similarity of the layer is calculated, and the calculation formula is as follows:
wherein, the maximum number of nodes refers to the maximum value of the number of nodes of the layer d of the same depth of T1 and T2.
After the similarity calculation of each layer depth is completed, summation is performed and is recorded as sum. The similarity of T1, T2 is calculated as follows:
according to the above calculation method, if the similarity between T1 and T2 is calculated to be 50%, it is indicated that approximately 50% of the nodes in T1 are matched with T2, and at this time, the matching between T1 and T2 is considered to be high. Therefore, 50% can be used as a threshold for confirming the matching of T1 and T2, that is, if the similarity of T1 and T2 is calculated to be higher than 50%, it can be considered that the matching of T1 and T2 is successful, that is, it can be further confirmed that the target website can match the website fingerprint F1. If T1 and T2 can be successfully matched, T2 is intercepted, nodes in the range of the height H are reserved and marked as T3, and corresponding information of F1-T3 at the moment is recorded.
After the similarity calculation of the T1 and the T2 is completed, continuing to traverse the T0 in a layering way, and circulating the calculation process to finally obtain a group of fingerprints matched by the T0 and the information of a new webpage map tree T3 corresponding to each fingerprint in the group of fingerprints.
In the step (5), updating the website fingerprint-website map tree bank specifically comprises the following steps: and (4) finally obtaining the fingerprints matched with the target websites and the information of the new webpage map tree T3 corresponding to each fingerprint, and updating the obtained information of the new website fingerprint-webpage map tree into a website fingerprint-webpage map tree library, so that the information of the website fingerprint-webpage map tree library can be further expanded, the coverage of the website fingerprint-webpage map tree library is increased, and the efficiency and accuracy for obtaining the website fingerprints are further improved.
The foregoing is merely a preferred embodiment of the present invention, and the present invention has been disclosed in the above description of the preferred embodiment, but is not limited thereto. Any person skilled in the art can make many possible variations and modifications to the technical solution of the present invention or modifications to equivalent embodiments using the methods and technical contents disclosed above, without departing from the scope of the technical solution of the present invention. Therefore, any simple modification, equivalent variation and modification of the above embodiments according to the technical substance of the present invention still fall within the scope of the technical solution of the present invention.
Claims (5)
1. The fingerprint identification method based on the sitemap is characterized by comprising the following steps of:
(1) Generating a sitemap tree: capturing a sitemap of a target website, and representing the sitemap by using an n-ary tree T0;
(2) Pruning the sitemap tree: pruning the sitemap tree T0 according to the website path blacklist, reserving a website path capable of reflecting website fingerprints, and generating a simplified sitemap tree;
(3) Establishing a website fingerprint-sitemap tree bank D1;
(4) Fingerprint identification: traversing a sitemap tree in a sitemap tree bank and matching with a target sitemap tree, thereby obtaining fingerprint information of a target website; setting a sitemap tree of a target website as T0, traversing each piece of data in D1 to obtain corresponding information of the website fingerprint-sitemap tree, setting the currently traversed website fingerprint as F1, setting the website map tree as T1, and matching the T0 and the T1, wherein the specific calculation method is as follows:
firstly, traversing the hierarchy T0, comparing val of the traversed node with val of a root node of T1, and if different, continuing traversing downwards; if the two nodes are the same, setting a tree taking the current node as a root node in T0 as T2, and then calculating the similarity between the T2 and the T1;
if the calculated similarity of the T1 and the T2 is higher than the similarity threshold, the T1 and the T2 can be considered to be successfully matched, and the target website can be further confirmed to be matched with the website fingerprint F1; if T1 and T2 can be successfully matched, intercepting T2, reserving nodes within the range of the height H of T1, recording as T3, and recording corresponding information of F1-T3 at the moment;
after the similarity calculation of the T1 and the T2 is completed, continuing to traverse the T0 in a layering way, and circulating the calculation process to finally obtain a group of fingerprints matched by the T0 and the information of a new webpage map tree T3 corresponding to each fingerprint in the group of fingerprints;
the specific method for calculating the similarity of T1 and T2 comprises the following steps:
performing hierarchical traversal from the root node of the T1, comparing the node val between the T1 and the T2 at the same layer, and ending the similarity calculation process after the T1 traversal is completed; recording the depth d of the root node as 0, and increasing the node depth from top to bottom in sequence; in each layer, the similarity of the layer is calculated, and the calculation formula is as follows:
the maximum number of nodes refers to the maximum value of the number of nodes of the layer d of the same depth of T1 and T2;
after the similarity calculation of each layer of depth is completed, summing and marking as sum;
the similarity calculation formula of T1 and T2 is as follows:
(5) Website fingerprint-sitemap tree bank update: and updating the corresponding information of the website fingerprint and the sitemap tree of the target website into a website fingerprint-sitemap tree bank.
2. The sitemap-based fingerprint identification method according to claim 1, wherein in the step (1), each node of the n-ary tree T0 has two attributes: the value val of the current node and the child node list child of the current node.
3. The sitemap-based fingerprint identification method according to claim 1, wherein in the step (2), a blacklist is established of general fields which cannot reflect characteristics of a website;
when a certain node of the sitemap tree exists in the blacklist, the node is cut off;
when the number of child nodes of a certain node of the sitemap tree is greater than a node threshold, the node is pruned.
4. The sitemap-based fingerprint identification method according to claim 1, wherein in the step (3), the sitemap-sitemap tree library construction method specifically comprises:
establishing a website fingerprint library D0 and storing a plurality of website fingerprints;
establishing a website fingerprint-website map tree library D1, and storing one-to-many relation between the website fingerprint and the website map tree;
for each website fingerprint in D0, finding a website corresponding to the website fingerprint, then obtaining a website map of the website, further obtaining a website map tree of the website, and adding the corresponding information of the website fingerprint-website map tree into D1.
5. The sitemap-based fingerprint identification method according to claim 1, wherein in the step (5), the fingerprint matched with the target website obtained in the step (4) and the information of the new sitemap tree T3 corresponding to each fingerprint are updated into a sitemap-sitemap tree bank, so that the information of the sitemap-sitemap tree bank is further expanded, and the coverage of the sitemap-sitemap tree bank is increased.
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