Manchun Tan

31 papers C 2Journal 25Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Neural Process. Lett.
Zili Jiang, Mingbing Luo, Manchun Tan
2026 J jnl
Math. Comput. Simul.
Qiu Peng, Manchun Tan, Mingbing Luo, Kai Wu
2025 J jnl
Neurocomputing
Qiu Peng, Xiaotang Zhang, Manchun Tan
2025 J jnl
Neurocomputing
Mingbing Luo, Zili Jiang, Manchun Tan
2025 C conf
ISNN
Manchun Tan, Weihao Du
2025 J jnl
Commun. Nonlinear Sci. Numer. Simul.
Qiu Peng, Siman Lin, Manchun Tan
2025 J jnl
Int. J. Syst. Sci.
Siman Lin, Xiaotang Zhang, Junwu Ren, Manchun Tan
2023 J jnl
IEEE Intell. Transp. Syst. Mag.
Xin Huang, Peiqun Lin, Chen Chen, Bin Ran, Manchun Tan
2023 J jnl
Neural Process. Lett.
Weihao Du, Jianglian Xiang, Manchun Tan
2023 J jnl
IEEE Trans. Intell. Transp. Syst.
Xin Huang, Peiqun Lin, Mingyang Pei, Bin Ran, Manchun Tan
2022 J jnl
Neurocomputing
Jianglian Xiang, Junwu Ren, Manchun Tan
2022 J jnl
Neurocomputing
Jianglian Xiang, Manchun Tan
2022 J jnl
Neural Process. Lett.
Jianglian Xiang, Manchun Tan
2021 J jnl
Concurr. Comput. Pract. Exp.
Manchun Tan, Zhiqiang Song, Yunfeng Liu, Zhong Li
2021 J jnl
Int. J. Control
Manchun Tan, Jieyin Mai, Zhiqiang Song
2019 J jnl
Neural Process. Lett.
Manchun Tan, Xiaojun Li, Yunfeng Liu
2019 J jnl
Int. J. Mach. Learn. Cybern.
Manchun Tan, Qi Pan
2019 J jnl
Math. Comput. Simul.
Yunfeng Liu, Zhiqiang Song, Manchun Tan
2019 J jnl
Appl. Math. Comput.
Manchun Tan, Yunfeng Liu, Desheng Xu
2018 J jnl
Kybernetika
Manchun Tan, Desheng Xu
2018 J jnl
Neurocomputing
Manchun Tan, Desheng Xu
2018 J jnl
Commun. Nonlinear Sci. Numer. Simul.
Desheng Xu, Manchun Tan
2017 conf
ISNN (1)
Jieyin Mai, Manchun Tan, Yunfeng Liu, Desheng Xu
2016 J jnl
Neural Process. Lett.
Manchun Tan
2016 C conf
ISNN
Manchun Tan, Desheng Xu
2016 J jnl
Neurocomputing
Long Jin, Yunong Zhang, Tianjian Qiao, Manchun Tan, Yinyan Zhang
2015 J jnl
Int. J. Comput. Intell. Syst.
Manchun Tan, Shuping Xu, Zhong Li
2013 conf
ISNN (1)
Huimin Liao, Manchun Tan, Shuping Xu
2012 conf
ISNN (1)
Zhen Zheng, Manchun Tan, Qunfang Wang
2010 J jnl
Neural Process. Lett.
Manchun Tan
2009 conf
ISNN (1)
Manchun Tan
redb/extractors/elf_extractors/elf_segments.py
← Index redb/extractors/elf_extractors/elf_segments.py python
import inspect
import hashlib
import math
from collections import Counter
from datetime import datetime, timezone
from typing import Any, List, Dict

from elftools.elf.elffile import ELFFile
from elftools.common.exceptions import ELFError

from redb.extractors.enum import Tag
from redb.extractors.elf_extractor import ELFExtractor
from redb.models.dataclasses import ELFSegment


class ELFSegmentExtractor(ELFExtractor):

    def __init__(
        self,
        filepath,
        log,
        exporters=None,
        index_prefix=None,
        elastic_index=None,
        known_benign=False,
        known_malicious=False,
        elf=None,
    ):
        super().__init__(
            filepath,
            log,
            exporters,
            index_prefix,
            elastic_index,
            known_benign,
            known_malicious,
            elf,
        )
        self.elf_segments = []
        self.elastic_index = self.index_prefix + "-elf_segments"
        self.log.debug(inspect.currentframe().f_code.co_name)

    def _is_empty_result(self, extracted_data) -> bool:
        """
        Override: Empty segments is an ERROR, not a valid empty case.
        A valid ELF file must have segments (program headers).
        """
        # Always return False - empty segments should be treated as an error
        return False

    def _calculate_entropy(self, data: bytes) -> float:
        """Calculate Shannon entropy of data."""
        if not data:
            return 0.0

        try:
            # Count frequency of each byte
            byte_counts = Counter(data)
            data_len = len(data)

            # Calculate entropy
            entropy = 0.0
            for count in byte_counts.values():
                if count > 0:
                    frequency = count / data_len
                    entropy -= frequency * math.log2(frequency)

            return entropy
        except Exception as e:
            self.log.error(f"Error calculating entropy: {e}")
            return 0.0

    def _map_segment_type(self, p_type_str: str) -> int:
        """Map segment type string to enum value."""
        type_map = {
            'PT_NULL': 0,
            'PT_LOAD': 1,
            'PT_DYNAMIC': 2,
            'PT_INTERP': 3,
            'PT_NOTE': 4,
            'PT_SHLIB': 5,
            'PT_PHDR': 6,
            'PT_TLS': 7
        }
        return type_map.get(p_type_str, 0)

    def _decode_segment_flags(self, flags: int) -> List[str]:
        """Decode segment flags to human-readable strings."""
        flag_strings = []

        if flags & 0x1:  # PF_X
            flag_strings.append('EXECUTE')
        if flags & 0x2:  # PF_W
            flag_strings.append('WRITE')
        if flags & 0x4:  # PF_R
            flag_strings.append('READ')

        return flag_strings if flag_strings else ['NONE']

    def _extract_segment_data(self, segment) -> ELFSegment:
        """Extract data from a single segment with granular error handling."""
        # Initialize with safe defaults
        segment_type = 0
        segment_type_str = 'unknown'
        segment_flags = 0
        segment_flags_str = ['NONE']
        segment_offset = 0
        segment_vaddr = 0
        segment_paddr = 0
        segment_filesz = 0
        segment_memsz = 0
        segment_align = 0
        segment_entropy = 0.0
        segment_sha256 = ""
        segment_md5 = ""

        # Try to get segment header
        header = None
        try:
            header = segment.header
        except Exception as e:
            self.log.warning(f"Could not access segment header: {e}")
            return ELFSegment(
                segment_type=segment_type, segment_type_str=segment_type_str,
                segment_flags=segment_flags, segment_flags_str=segment_flags_str,
                segment_offset=segment_offset, segment_vaddr=segment_vaddr,
                segment_paddr=segment_paddr, segment_filesz=segment_filesz,
                segment_memsz=segment_memsz, segment_align=segment_align,
                segment_entropy=segment_entropy, segment_sha256=segment_sha256,
                segment_md5=segment_md5
            )

        # Extract segment type
        try:
            p_type_str = header.get('p_type', 'PT_NULL')
            segment_type = self._map_segment_type(p_type_str)
            segment_type_str = p_type_str.replace('PT_', '') if p_type_str.startswith('PT_') else p_type_str
        except Exception as e:
            self.log.warning(f"Could not extract segment type: {e}")

        # Extract segment flags
        try:
            segment_flags = header.get('p_flags', 0)
            segment_flags_str = self._decode_segment_flags(segment_flags)
        except Exception as e:
            self.log.warning(f"Could not extract segment flags: {e}")

        # Extract segment addresses and sizes
        try:
            segment_offset = header.get('p_offset', 0)
        except Exception as e:
            self.log.warning(f"Could not extract segment offset: {e}")

        try:
            segment_vaddr = header.get('p_vaddr', 0)
        except Exception as e:
            self.log.warning(f"Could not extract segment vaddr: {e}")

        try:
            segment_paddr = header.get('p_paddr', 0)
        except Exception as e:
            self.log.warning(f"Could not extract segment paddr: {e}")

        try:
            segment_filesz = header.get('p_filesz', 0)
        except Exception as e:
            self.log.warning(f"Could not extract segment filesz: {e}")

        try:
            segment_memsz = header.get('p_memsz', 0)
        except Exception as e:
            self.log.warning(f"Could not extract segment memsz: {e}")

        try:
            segment_align = header.get('p_align', 0)
        except Exception as e:
            self.log.warning(f"Could not extract segment align: {e}")

        # Calculate entropy and hashes for segment data (most likely to fail)
        try:
            if segment_filesz > 0:
                segment_data = segment.data()
                if segment_data:
                    # Calculate entropy
                    segment_entropy = self._calculate_entropy(segment_data)

                    # Calculate hashes
                    segment_sha256 = hashlib.sha256(segment_data).hexdigest()
                    segment_md5 = hashlib.md5(segment_data).hexdigest()
        except Exception as e:
            self.log.warning(f"Could not read segment data for hashing: {e}")
            # Keep defaults (0.0, "", "")

        return ELFSegment(
            segment_type=segment_type,
            segment_type_str=segment_type_str,
            segment_flags=segment_flags,
            segment_flags_str=segment_flags_str,
            segment_offset=segment_offset,
            segment_vaddr=segment_vaddr,
            segment_paddr=segment_paddr,
            segment_filesz=segment_filesz,
            segment_memsz=segment_memsz,
            segment_align=segment_align,
            segment_entropy=segment_entropy,
            segment_sha256=segment_sha256,
            segment_md5=segment_md5
        )

    def tag(self):
        return Tag.ELF_SEGMENTS.value if hasattr(Tag, 'ELF_SEGMENTS') else "elf_segments"

    def extract(self):
        try:
            self.log.debug(inspect.currentframe().f_code.co_name)

            def extract_segments(elf):
                segments_data = []

                # Iterate through all segments with per-segment error handling
                for segment_index, segment in enumerate(elf.iter_segments()):
                    try:
                        segment_data = self._extract_segment_data(segment)
                        if segment_data:
                            segments_data.append(segment_data)
                        else:
                            self.log.warning(f"Failed to extract data for segment {segment_index}")
                    except Exception as e:
                        self.log.warning(f"Error processing segment {segment_index}: {e}")
                        # Continue processing other segments

                return segments_data

            # Check if file is valid ELF
            if not self._is_elf_file():
                self.log.error(f"No valid ELF file for {self.hash.sha256}")
                return None

            segments_data = self._with_elf_file(extract_segments)
            if segments_data is None:
                return None

            self.elf_segments = segments_data
            return self.elf_segments

        except Exception as e:
            self.log.error(f"Error extracting ELF segments {self.hash.sha256}: {e}")
            return None

    def prepare_export_data(self, exporter_type: str) -> Any:
        self.log.debug(inspect.currentframe().f_code.co_name)

        if exporter_type == "ElasticsearchExporter":
            return self.elf_segments
        elif exporter_type == "ClickHouseExporter":
            try:
                if not self.elf_segments:
                    return None

                # Prepare data arrays for all segments
                data = []
                current_time = datetime.now(timezone.utc)
                for segment in self.elf_segments:
                    row = [
                        self.sha256,
                        self.md5,
                        self.sha1,
                        segment.segment_type,
                        segment.segment_type_str,
                        segment.segment_flags,
                        segment.segment_flags_str,
                        segment.segment_offset,
                        segment.segment_vaddr,
                        segment.segment_paddr,
                        segment.segment_filesz,
                        segment.segment_memsz,
                        segment.segment_align,
                        segment.segment_entropy,
                        segment.segment_sha256,
                        segment.segment_md5,
                        current_time
                    ]
                    data.append(row)

                column_names = [
                    'sha256', 'md5', 'sha1',
                    'segment_type', 'segment_type_str', 'segment_flags', 'segment_flags_str',
                    'segment_offset', 'segment_vaddr', 'segment_paddr',
                    'segment_filesz', 'segment_memsz', 'segment_align',
                    'segment_entropy', 'segment_sha256', 'segment_md5',
                    'analysis_date'
                ]

                column_type_names = [
                    'FixedString(64)', 'FixedString(32)', 'FixedString(40)',
                    "Enum8('NULL'=0, 'LOAD'=1, 'DYNAMIC'=2, 'INTERP'=3, 'NOTE'=4, 'SHLIB'=5, 'PHDR'=6, 'TLS'=7)",
                    'LowCardinality(String)',
                    'UInt32',
                    'Array(LowCardinality(String))',
                    'UInt64', 'UInt64', 'UInt64', 'UInt64', 'UInt64', 'UInt64',
                    'Float64',
                    'FixedString(64)', 'FixedString(32)',
                    'DateTime64(3, \'UTC\')'
                ]

                if not data:
                    return None

                return (data, column_names, column_type_names)

            except Exception as e:
                self.log.error(f"Error preparing export data: {e}")
                raise

    def get_clickhouse_table(self) -> str:
        return "redb_elf_segments"